Systems approach to comorbidity assessment

ABSTRACT

Methods, systems, and apparatus for assessing a state of a comorbidity associated with a primary disease are provided. The methods comprise receiving at least one autonomic index, neurologic index, stress marker index, psychiatric index, endocrine index, adverse effect of therapy index, physical fitness index, or quality of life index of a patient; comparing the at least one index to at least one reference value; and assessing a state of a body system of the patient that is a site of the comorbidity, based on the comparison. A computer readable program storage device encoded with instructions that, when executed by a computer, perform the method described above is also provided. A medical device system capable of implementing the method described above is also provided.

This application is related to an application filed concurrentlyherewith, entitled “A Systems Approach to Disease State and HealthAssessment,” having the same inventor, the disclosure of which is herebyincorporated herein by reference.

FIELD OF THE INVENTION

This invention relates generally to medical device systems and, moreparticularly, to medical device systems and methods capable of assessinga state of a disease.

DESCRIPTION OF THE RELATED ART

Diseases or disorders and their treatments, if available, often have adeleterious impact on the patient's overall health and well being.Traditionally, medical practice focuses its diagnostic and therapeuticefforts to the specific disorder (primary diagnosis), an approach thatwhile necessary and, in at least certain ways, useful, ignores the“spill-over” effect of the disease or treatment on the patient's overallhealth and well being. By compartmentalizing diseases, a reductionistpractice, medicine as presently practiced ignores the substantial andfundamental loss of information inherent to this approach. That is,fragmenting into its constituents parts complex, non-linear networksystems (of which the human body is a paradigm) so as to facilitatetheir study. This fragmentation will often lead to imprecise anddistorted findings because the assembly of systems (which determinesoverall health) is greater than the sum of its parts. This viewpointcentral to general systems theory applies to various embodiments of thepresent invention. For example, embodiments disclosed herein illustratehow the deleterious impact on the patient as a whole is a function ofthe disease type, its rate of progression, severity, and duration, andof the type of therapy and its dose. Clearly, the impact is often moresevere or complicated when the patient has multiple disease types orseveral therapies.

Various elements of the system interact through interconnected feed-backand feed-forward loops. FIG. 16, for example, illustrates the complexnature of the primary disease of obesity where feed-forward andfeed-back loops can accelerate the progression of the disease. FIG. 17provides a similar example for the primary disease of epilepsy.Embodiments of the present invention utilize systems theory's tenets byrecognizing and incorporating a primary disease or disorder with itsco-morbidities. Numerous embodiments of the present inventiondemonstrate how largely positive feed-forward and feed-back loopsbetween diseases or disorders and their expected mutually amplifyingeffects result in wide variations of disease/disorder progression orregression. Further, the potential for transmutability andcontext-dependency of whether a disorder or disease is a primary one ora co-morbidity is apparent through the example of how obesity may becomea co-morbidity in subjects treated for epilepsy.

Obesity and its co-morbidities together provide a non-limiting examplethat illustrates how undesired “spillover” effects from a primarydisease or condition under consideration can negatively impact thepatient's health. Obesity is a disorder of epidemic proportions in theUS, and substantially increases the patient's risk of developingdiabetes mellitus, arterial hypertension, hyperlipidemia and obstructivesleep apnea, while shortening life span and degrading quality of life.Arterial hypertension, diabetes and hyperlipidemia, in turn, accelerateatherosclerosis, which further increases the risks for myocardialinfarction, stroke, congestive heart failure, and avascular gangrene.Similarly, obstructive sleep apnea causes intractable arterialhypertension, atrial fibrillation, cognitive deterioration, depression,sexual dysfunction, and chronic headaches.

This exemplary list of a primary disorder (e.g., obesity, FIG. 16) andits “co-morbidities” illustrates how the human body may be considered asa densely interconnected (bidirectional) network of “nodes” (bodysystems and/or organs), stressing the dependence of its complex dynamicson the integrity of each of its component “nodes”. The interactionsamong the nodes may be viewed as feed-forward or feedback loops thatunder pathological conditions have an amplifying effect or “positive”(e.g., positive feedback) effect on themselves and on the network. A“systems” approach to human disease which would acknowledge theanatomical and functional interconnections one organ or body system'sfunction has on the others, is lacking in the field of health care, tothe detriment of quality of care and cost-effectiveness. Such a“systems” approach, exemplified by embodiments of the present invention,provides for the systematic and reproducible means of automaticallytracking the evolution of the primary disease or disorder (e.g.,obesity) and of its co-morbidities (e.g., hypertension, diabetes, sleepapnea, etc.) to identify or preferably anticipate their contribution toany change in the patient's overall health. Embodiments of the inventionmay be used either to prevent the emergence of co-morbidities, toameliorate their deleterious impact, and/or to improve or stabilizethem. As a result, it is possible to improve or preserve health andquality of life of the patient while lessening the upwardly spiralingcosts of health care.

While many diseases, their co-morbidities, or side effects of treatmentmay negatively affect the general health and well-being of a patient,only a handful of other examples will be furnished herein. Such examplesshould not be construed as limiting the scope of invention but, on thecontrary, merely to serve as examples underscoring the widespreadapplicability and usefulness of the invention.

Epilepsy affects approximately 60 million people worldwide of whomroughly 23 million are resistant to multiple medications.Pharmaco-resistant seizures are associated with an increase in mortalityand morbidity rates (compared to the general population and toepileptics whose seizures are controlled by medications) eventualimpairment of cognitive functions and mental health and with markedlydegraded quality of life for patients and their families. Seizures mayimpair motor control, responsiveness to a wide class of stimuli, andother cognitive functions. The sudden onset of a patient's impairment ofmotor control, responsiveness, and other cognitive functions precludesthe performance of necessary and even simple daily life tasks such asdriving a vehicle, cooking, or operating machinery, as well as morecomplex tasks such as acquiring knowledge and socializing. In the USAalone, the annual cost of epilepsy care is over USD 15 billion (in 1995dollars), most of which is attributable to subjects withpharmaco-resistant seizures. Certain pharmacological agents used fortreatment of epilepsy cause osteoporosis, reproductive dysfunction,liver, bone marrow, kidney, and skin damage, neurologic and psychiatricdysfunction, weight gain and in rare cases, death. Various epilepsytherapies, such as thermal manipulation of epileptogenic tissue orlocal/direct delivery of drugs to it, may also cause adverse effects,such as neurologic, autonomic, psychiatric, sleep, appetite, sex drive,and other disturbances.

Diabetes mellitus, a highly prevalent disease, causes autonomicdysfunction, accelerates atherosclerosis and with it the incidence ofheart attacks, strokes and avascular gangrene and has a negative impacton quality of life and mental health. In patients with juvenile or TypeI diabetes, the physiological responses to counteract hypoglycemia (acommon adverse effect of insulin) become blunted or absent making thisserious condition asymptomatic. That is, the symptoms that make a personaware that blood sugar is low—and which motivate or compel the person toeat—do not occur in these patients, considerably increasing the risks ofbrain damage and death due to hypoglycemia.

Parkinson's is a disease of the brain's basal ganglia, whose mainfunction is modulation of posture and movements. Parkinson's isassociated with autonomic dysfunction and increased risks of injury,dementia, and head and bodily injuries caused by falls. Autonomicdysfunction, in turn, increases the risk of cardiac arrhythmias,syncope, and death, with falls enhancing this risk. These selectedexamples underscore the importance of developing and implementing whatis referred herein as a systems approach to diseases, where the diseasein question and its impact on the other body organs and functions(co-morbidities), are assessed as a function of time and space-state andthis information is used for early intervention so as to preventdeterioration and further disabilities.

Co-morbidities are common with many other disorders or diseases, furtherimposing psycho-social and/or financial burdens on the patient, thepatient's family, and society in general, and worsening quality of life.Other costly and highly burdensome diseases or disorders includecardiovascular disorders (such as congestive heart failure and atrialfibrillation), respiratory disorders such as chronic obstructivepulmonary disease, depression and other mood disorders, schizophrenia,anxiety disorders and other neuropsychiatric disorders,neuro-degenerative diseases such as Alzheimer's, traumatic brain injury,migraine headache, eating disorders (such as obesity, anorexia nervosa,and bulimia), sleep disorders, hypertension, and pain (includingneuropathic pain and fibromyalgia).

Regardless of the disease in question, it would be useful to assess theevolution of the patient's primary disease and comorbidities throughcharacterization of their direction (progression, regression, orstabilization), magnitude, and rate of change and comorbidities, sincedisease progression is usually correlated with emergence of new orworsening of existing comorbidities, further degrading the patient'shealth and well-being. For example, certain types and severities ofepilepsy are associated with changes (compared to the generalpopulation) in the occurrence of sudden unexpected death (SUDEP),serious accidents, or other fatal events, such as suicide. It would beuseful to assess the clinical evolution of a patient's epilepsy and itsco-morbidities to determine the type(s) of risk(s) and their probabilityof occurrence to either revert the trend, if possible, and if not, toinstitute measures to minimize and manage those risks. No automatedsystem for making this assessment, determination, and risk management isknown to this inventor at this time.

Although treatment options for many diseases exist, the efficacy of aparticular treatment option for a particular disease in a particularpatient may be unpredictable. Further, the efficacy of a particulartreatment option for a particular disease in a particular patient may bedifficult to gauge, and further, such gauging may be subjectivelydetermined by the patient, the physician, or a combination thereof.Also, a particular treatment option for a particular disease in aparticular patient may lead to various side effects, some of which maybe difficult to gauge.

It would be desirable to have methods and apparatus to reproducibly andin a clinically useful and cost-effective manner: a) assess a state of adisease of a patient, such as a disease that impacts, directly orindirectly, a neurological, autonomic, endocrinologic, or psychiatricdisease and extent to which they impair overall health and well beingvia the emergence of “co-morbidities”; b) assess the therapies' sideeffects; c) improve or stabilize a existing disease and prevent theemergence of co-morbidities; d) prevent or ameliorate adverse treatmenteffects. The direct clinical and psychosocial benefits to patients andthe ensuing decrease in the financial burden to the health care systemand society of successfully implementing said automated comprehensiveassessment are readily apparent. The state of the art lacks anefficient, systematic, and user-friendly automated system for makingthis assessment. Desirably, an apparatus used in assessment would beimplantable or portable and operate in real-time or off-line. It wouldalso be desirable for such an apparatus to incorporate and analyze, forpurposes of assessing disease state, data obtained using otherdiagnostic devices including those that are not portable, implantable,or implementable into hardware or software. The assessment may be madeby an apparatus automatically and this either contingently (e.g.,triggered by a large or sudden change in an index, or by a patient's orcaregiver command) or at predetermined times; the assessment may be alsomade based on clinical judgment. The assessment may be quantitative(magnitude and rate), semiquantitative (questionnaires, subjectivescales), or qualititative (e.g. small, slow, etc).

SUMMARY OF THE INVENTION

In one embodiment, the present invention provides a method for assessinga comorbidity associated with a primary disease. In one embodiment, themethod comprises receiving at least one of an autonomic index, aneurologic index, a stress marker index, a psychiatric index, anendocrine index, a physical fitness index, or a quality of life index ofa patient; comparing the at least one index to at least one referencevalue associated with the at least one index; assessing a state of abody system of the patient based on the comparing, wherein the bodysystem comprises at least one of an autonomic system, a neurologicsystem, a psychiatric system, an endocrine system, or subsystems of theforegoing; and providing an output relating to the assessment, whereinthe output comprises at least one of body system stability, body systemimprovement, body system regression, or a finding that a state of thebody system cannot be determined, wherein the body system is a site ofthe comorbidity.

In one embodiment, the present invention provides a computer readableprogram storage medium encoded with instructions that, when executed bya computer, perform a method as described above.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention may be understood by reference to the followingdescription taken in conjunction with the accompanying drawings, inwhich like reference numerals identify like elements, and in which:

FIG. 1 illustrates a flowchart depiction of a method for assessing astate of a patient's disease, in accordance with an illustrativeembodiment of the present invention;

FIG. 2 illustrates a flowchart depiction of a method for assessing astate of a patient's disease, in accordance with an illustrativeembodiment of the present invention;

FIG. 3A provides a stylized diagram of a medical device implanted into apatient's body, in accordance with one illustrative embodiment of thepresent invention;

FIG. 3B provides a stylized diagram of a medical device implanted into apatient's body, in accordance with one illustrative embodiment of thepresent invention;

FIG. 3C provides a stylized diagram of a medical device implanted into apatient's body, in accordance with one illustrative embodiment of thepresent invention;

FIG. 4 is a block diagram of an implantable medical device system, inaccordance with one illustrative embodiment of the present invention;

FIG. 5 is a block diagram of a medical device system that includes amedical device and an external unit, in accordance with one illustrativeembodiment of the present invention;

FIG. 6 is a stylized block diagram of an autonomic index unit of amedical device or medical device system, in accordance with oneillustrative embodiment of the present invention;

FIG. 7 is a stylized block diagram of a neurologic index unit of amedical device or medical device system, in accordance with oneillustrative embodiment of the present invention;

FIG. 8 is a stylized block diagram of a kinetic capability determinationunit of a medical device or medical device system, in accordance withone illustrative embodiment of the present invention;

FIG. 9 is a stylized block diagram of a stress marker index unit of amedical device or medical device system, in accordance with oneillustrative embodiment of the present invention;

FIG. 10 is a stylized block diagram of a psychiatric index unit of amedical device or medical device system, in accordance with oneillustrative embodiment of the present invention;

FIG. 11 is a stylized block diagram of an endocrine index unit of amedical device or medical device system, in accordance with oneillustrative embodiment of the present invention;

FIG. 12 is a stylized block diagram of an adverse effect of therapyindex unit of a medical device or medical device system, in accordancewith one illustrative embodiment of the present invention;

FIG. 13 is a stylized block diagram of an index comparison unit of amedical device or medical device system, in accordance with oneillustrative embodiment of the present invention;

FIG. 14 is a stylized block diagram of an assessment unit of a medicaldevice or medical device system, in accordance with one illustrativeembodiment of the present invention;

FIG. 15 is a stylized block diagram of a forecast unit of a medicaldevice or medical device system, in accordance with one illustrativeembodiment of the present invention;

FIG. 16 is a stylized diagram of relationships between obesity and someof its comorbidities, with the direction of an arrow showing a source'stendency to increase or make more likely a target; and

FIG. 17 is a stylized diagram of relationships between epilepsy and someof its comorbidities, with the direction of an arrow showing a source'stendency to increase or make more likely a target.

While the invention is susceptible to various modifications andalternative forms, specific embodiments thereof have been shown by wayof example in the drawings and are herein described in detail. It shouldbe understood, however, that the description herein of specificembodiments is not intended to limit the invention to the particularforms disclosed, but on the contrary, the intention is to cover allmodifications, equivalents, and alternatives falling within the spiritand scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

Illustrative embodiments of the invention are described herein. In theinterest of clarity, not all features of an actual implementation aredescribed in this specification. In the development of any such actualembodiment, numerous implementation-specific decisions must be made toachieve the design-specific goals, which will vary from oneimplementation to another. It will be appreciated that such adevelopment effort, while possibly complex and time-consuming, wouldnevertheless be a routine undertaking for persons of ordinary skill inthe art having the benefit of this disclosure.

This document does not intend to distinguish between components thatdiffer in name but not function. In the following discussion and in theclaims, the terms “including” and “includes” are used in an open-endedfashion, and thus should be interpreted to mean “including, but notlimited to.” Also, the term “couple” or “couples” is intended to meaneither a direct or an indirect electrical connection. “Direct contact,”“direct attachment,” or providing a “direct coupling” indicates that asurface of a first element contacts the surface of a second element withno substantial attenuating medium there between. The presence of smallquantities of substances, such as bodily fluids, that do notsubstantially attenuate electrical connections does not vitiate directcontact. The word “or” is used in the inclusive sense (i.e., “and/or”)unless a specific use to the contrary is explicitly stated.

The term “electrode” or “electrodes” described herein may refer to oneor more stimulation electrodes (i.e., electrodes for delivering atherapeutic signal generated by an IMD to a tissue), sensing electrodes(i.e., electrodes for sensing a physiological indication of a patient'sbody), and/or electrodes that are capable of delivering a therapeuticsignal, as well as performing a sensing function.

This invention makes uni-variate (e.g., neurological index only) ormultivariate (e.g., neurological, autonomic, psychiatric, etc.)comparisons of the effects of the patient's disease state (and, in someembodiments, a treatment for the patient's disease) on one or more bodysystems. Comparisons may include one or more index parameters associatedwith body systems. Index parameters may involve measures of centraltendency, measures of dimensionality including fractal dimensionality,measures of non-linearity, measures of non-stationarity, measures oflong-range dependence or correlation, and measures of clustering, suchas the pseudo F statistic, including size, shape number and distancebetween clusters. The index parameters may also comprise distributionsof any of the foregoing measures.

The index measures may be treated separately or as a composite (i.e., asingle measure of multivariate indices). Where a composite measure isused, the component indices may be weighted differently based on itsimpact on subject's well-being or safety, and may be derived fromindices obtained from either implanted or external devices, or fromhistorical data.

Comparisons may be intra-subject or inter-subject, including to tablesof normative values from healthy or special populations, and may beperformed as a function of time or state space. Comparisons may bequantitative and associated with a statistical significance value orqualitative or based on clinical judgment. The analyses performed aspart of embodiments of this invention will yield four quantitative orqualitative outcomes: disease progression (deterioration in the index)expressed as one of a numerical difference in relation to past values, arate of change of the index as a function of time from the previousmeasurements, or a qualitative change (e.g., minimal and slow or markedand rapid); disease stabilization (no change in the index); diseaseregression (improvement in the index); or insufficientinformation/undecidable. The outcomes will be automaticallytime-stamped, reported and stored for comparisons with past and futuremeasurements, along with the index values and comparison results leadingto the quantitative, semi-quantitative or qualitative outcome reportedfor the index. Models of disease state may be built to issue forecastsor prognoses of the patient's future condition or disease state, usingtools or methods (e.g., Kalman filtering, Bayesian statistics, etc.)known to the person of ordinary skill in the art. Changes in indexvalues relative to past or normative data may also be used to stratifypatients into risk categories. Automated warnings may be issued foreither large or rapid deterioration (indicative of disease progression)in any of the index value at the time it is observed or detected orforecast so that treatment or preventive measures may be instituted.

Embodiments of the present invention provide for assessing a state of adisease of a patient. In some embodiments, one or more of an autonomicindex, a neurologic index, a stress marker index, a psychiatric index,an endocrine index, an adverse effect of therapy index, a physicalfitness index, and/or a quality of life index may be compared topredetermined or corresponding reference values. The assessment of thedisease may be performed based upon the comparisons of the indices torespective reference values.

Any disease may be considered herein. As discussed above, it should beapparent that various diseases may coexist in a positive feedback loop.The term “primary disease” may be used herein to refer to a diseasewhich is the subject of medical attention. For example, for a patienthaving both epilepsy and congestive heart failure, a neurologist mayconsider epilepsy a primary disease and congestive heart failure asecondary disease or comorbidity; whereas a cardiologist may considerthe opposite.

As should be apparent, the methods and systems of the present inventionmay be applied in situations where one or more diseases are the subjectof medical attention. For example, the methods of the present inventionmay be used by a patient suffering from epilepsy to monitor the state ofthis disease and any comorbidities associated with it. For anotherexample, the methods of the present invention may be used by a patientsuffering from both epilepsy and diabetes mellitus to monitor the stateof each disease and any comorbidities associated with either disease. Aswill be apparent to the person of ordinary skill in the art having thebenefit of the present disclosure, the states of any one or more knowndiseases, including but not limited to the exemplary ones referred toabove, and their associated comorbidities may be monitored.

As will be described in further details below, FIG. 1 shows oneexemplary embodiment of a method according to the present invention. Oneor more of an autonomic index, a neurologic index, a stress markerindex, a psychiatric index, an endocrine index, an adverse effect oftherapy index, a physical fitness index, and/or a quality of life (QOL)index are determined during a first time period at steps 112, 114, 115,116, 117, and/or 119. Similarly, one or more of an autonomic index, aneurologic index, a stress marker index, a psychiatric index, anendocrine index, an adverse effect of therapy index, a physical fitnessindex, and/or a quality of life (QOL) index are determined during asecond time period at steps 122, 124, 125, 126, 127, 128, and/or 129.Thereafter, at least two indices are compared to respective referencevalues across the first and second time periods at step 130.

In addition to time, “space states” can be used to define conditions inwhich the index values are determined. Herein, “space states” refer toindex values as measured at different locations in or on the patient'sbody, or in the same location but during different states (e.g,wakefulness vs. sleep; sedentary or resting conditions vs. exercise).For example, the patient's oxygen saturation can be measured by a pulseox device, such as fingertip-mountable oxygen saturation sensor, andsimultaneously the patient's heart rate can be measured by anappropriate device, such as an implantable medical device. For anotherexample, the patient's oxygen saturation can be measured during aresting condition and during physical exertion. An index can comprisedata from one or more locations in or on the body collected at one ormore times.

Assessments of disease state or comorbidity based on tests, scales, orquestionnaires may be administered automatically on-line or off-line.Adaptation and validation of said tests, scales or questionnaires may beperformed as needed to ensure reproducibility and proper interpretation.

Once the comparison is made, a determination 140 is made whether thecomparison can support the conclusion that the patient's disease and/ora state of a body system of the patient has changed or remained stable.If not, an indication 145 is made that no conclusion about the patient'sdisease and/or a body system of the patient can be made.

Optionally, the indication 145 of no conclusion can further comprisereporting one or more reasons for the indication; e.g., the sample sizeis too small, the data is too noisy, or the analysis is too complex tobe performed.

If the comparison can support the conclusion that the patient's diseaseand/or a state of a body system of the patient has changed or remainedstable, a determination 146 is made whether the patient's disease and/ora state of a body system of the patient has changed. If it has not, anindication 147 is made that the patient's disease and/or a body systemof the patient is stable.

However, if the comparison indicates the patient's disease and/or astate of a body system of the patient has changed, then a determination150 is made whether the patient's disease has progressed or regressedrelative to a previous assessment and/or whether the patient's bodysystem has improved or worsened relative to a previous assessment.

As will be described in further details below, FIG. 2 shows anotherembodiment of a method according to the present invention. In thisembodiment, one or more index values are acquired 210, and valuesderived from measure(s) of central tendency are computed 215 and/orother features (e.g., dimensionality, stationarity, clustering, longrange dependencies, fractality, etc.) are determined 220. Thereafter,the features are compared to a reference value, in a quantitative manner230 (such as statistically or non-statistically) and/or asemi-quantitative or qualitative (e.g., reflective of clinical judgment)manner 235.

A determination 240 is then made as to whether the comparison shows achange. If the determination is “no,” the disease or body system isconsidered stable (box 250). If the determination is “yes,” themagnitude, direction, and/or rate of change is determined 260, fromwhich the state of the disease or body system can be assessed 265. Ifdesired, the patient's overall health may be assessed 270, in light ofthe disease state, body system state, and/or other parameters.Alternatively or in addition, a risk of a negative outcome, such as riskof death, disease progression, new comorbidity, or the like can bereported 280.

From the comparisons, parametric or non-parametric statistical tests maybe applied to measures of central tendency or to distributions thereof.Such tests include, but are not limited to, Student's t-test, Fisher'stest, ANOVA, the Kolmogorov-Smirnoff, or the Mahalanobis, among others.If the measure(s) of central tendency or the distribution(s) arestatistically significantly different, the magnitude and direction ofthe deviation may be estimated using appropriate tests or measures.Additionally or alternatively, clinical judgment may be applied todetermine if the changes (whether or not statistically significant) areworthy of attention and merit intervention. Analyses may be performed onthe mean, median, standard deviation, coefficient of variation, nthpercentile, or any other measure of central tendency of a statisticaldistribution of index values. Analyses may be performed, whenapplicable, using spectral analysis, high order spectral analysis,detrended fluctuation analysis, fractal analysis, multifractal analysis,correlation dimension, and combinations thereof. Other techniques, suchas regression analyses, eigen methods (e.g. principal component andcanonical correlation analysis), co-variance analyses, bootstrapping, orMonte Carlo may be also used, among others known to the person ofordinary skill in the art.

Generally, biological data is non-stationary (the statistical propertieschange as function of time) and has long-range dependence (the values orcharacteristics of the present datum depend on previous data values). Avariable or observable is considered “stationary” if all of itsstatistical parameters are independent of time. Most statisticaltechniques are well suited for data that is stationary, but certainvariables or observables (e.g. heart rate and heart rate variability)that can be used in this invention to assess disease state, are to somedegree nonstationary or cyclo-stationary. The “identically distributed”assumption is violated when the sampled process is non-stationary,which, for example, can cause the sample mean to be under- orover-estimated.

A two prong approach can be used to maximize the information contentextracted from the analyses and of non-stationary data to better assessdisease state: 1. Minimization of non-stationarity and of long-rangedependencies to obtain information devoid of certain external influencesor perturbations that best reflect the body system's “static” behavior;2. Utilization of methods that address non-stationarity and long-rangedependence to gain insight into the body system's behavior underexternal influences. Approaches to manage or minimize non-stationarity(e.g., stratification) so that the data may be analyzed usingconventional statistics are well known to those skilled in the art andcan be applied to extract valuable insights into disease state.

Certain data (e.g., EKG, EEG) used in this invention to assess diseasestate have “memory” which manifests as long range dependences. That is,values are not independent from each other such that present values areinfluenced by past ones. Estimation of the Hurst exponent and DetrendedFluctuation analysis may be used, among other methods, to characterizethese type of data.

On the assumption a healthy subject's body is continually responding tochanges in the environment, changes in the degree of non-stationarityand in long-range dependence in a biological time series, especiallydecreases in non-stationarity and/or long-range dependence, are usuallyindicative of dysfunction.

Time-frequency methods may be also applied to the analyses andprocessing (including detection, estimation, filtering, etc) ofnonstationary processes that are some of the subject matter of thisinvention. The methods include but are not limited to the time-frequencyautoregressive moving-average (TFARMA) model, as well as its specialcases, the TFAR and TFMA models as they are computationally efficientand stable, retaining the simplicity and intuitiveness of the powerspectral density. The coherent and incoherent statistics based in thesample coherence statistic (that apply a measure of fitness) and othermethods based on the theory of periodically correlated (cycloperiodic)processes are particularly useful for analyses of biological data (e.g.,heart rate variability, cortisol levels) subject to circadianvariations.

Other methods that can be used include the heterogeneous autoregressive(HAR) models, the autoregressive moving average process of order (p,q)(ARMA(p,q) process), the autoregressive integrated moving averageprocess of order (p,d,q) (ARIMA (p,d,q), the autoregressive fractionallyintegrated moving average process (ARFIMA(p,d,q) process), and thevector fractionally integrated autoregressive moving-average (VARFIMA)model.

The smooth localized complex exponentials (SLEX) model may be alsoapplied and the best model can be selected using the penalized logenergy criterion, which may be derived to be the Kullback-Leiblerdistance between a model and the SLEX principal components of themultivariate time series.

Certain data (e.g., EKG, EEG) used in this invention to assess diseasestate have “memory” which manifests as long range dependences.Estimation of the Hurst exponent and Detrended Fluctuation analysis maybe used, among other methods, to characterize these type of data.

From this information, a prognosis formulated on the degree and rate of,e.g., cognitive changes is determined 260, the prognosis or a calculatedprobability of a serious outcome (e.g. mortality or extreme morbidity)265, and/or a probability of an accident or injury 270, are estimatedand provided to a predesignated person(s) so that appropriate and timelyaction(s), including preventive ones, may be taken. Models may built tosimulate the temporal evolution of the various indices and, using thesemodels, the probability estimates of various outcomes may be optimized.

In one embodiment, the present invention provides a method, apparatusand system to perform assessment of a state of a primary disease and/orco-morbidities of a patient and use these data to assess the patient'sstate of health and well-being. Embodiments disclosed herein call forreceiving at least one first autonomic index, neurologic index, stressmarker index, psychiatric index, an endocrine index, a physical fitnessindex, or quality of life index of a patient. The embodiments disclosedherein may also comprise receiving at least one second autonomic index,neurologic index, stress marker index, psychiatric index, endocrineindex, physical fitness index, or quality of life index of the patient.

As used herein, the term “signals” includes (i) the “raw” signal (e.g.,EKG) as recorded with a device, or parts or components of said signal(e.g., R-wave peaks), (ii) features derived from the “raw” signal usingstatistical, mathematical, or spectral tools (e.g., heart ratevariability derived from R wave intervals, heart rate variabilitytriangular index, SDNN, pNN50, LF, HF, LF/HF, etc.), (iii) therelationship the signal has with other signals or events, such aschanges in heart rate as a function of respiratory frequency and/ortidal volume; and (iv) any recordable output such as cognitivefunctions, electrical, chemical, mechanical, thermal, or acousticsignals or any other information that may be used on any time scale toinfer or extract useful information, about the state of a subject or ofany of his organs. The signals may be analog or digital and can beconverted therebetween as a routine matter for the person of ordinaryskill in the art having the benefit of the present disclosure.

For example, in the case of EKG, this signal can be compared to itself(e.g., compiling a master EKG signal by combining parallel EKG signalsdetected from electrodes), compared to another body signal (e.g.,aligning R waves of the EKG to respiration patterns or EEG patterns), orcompared to events or non-body signals (e.g., EKG variations due tocircadian rhythms, stress, exercise, or emotions). Similarly, other bodysignals discussed herein contain a myriad of information packed into thesignal. The term “signal” is used herein to include all of thisadditional information that can be extracted or inferred from the signaland not simply the raw signal alone.

In another embodiment, one or more windows vary in window length as afunction of time, disease state, another variable, or parameter.

In one embodiment, three or more windows are used to allow thecomparison of isolated periodic events in the patient's life. Forexample, the system can compare indices by stratifying data andcomparing one night to previous night(s) or designated times (e.g, 12:00AM-06:00 AM, to the same time interval. Similarly, the system cancompare day to previous day(s), REM sleep to prior REM sleep, morning toprior morning(s), cardiovascular exercise to previous cardiovascularexercise session(s), etc. as a function of ultradian, circadian, “lunar”or other rhythms. Comparisons may be made as a function of ultradian,circadian, “lunar” or other rhythms and between similar strata ordifferent strata.

In one embodiment, the first index has two or more windows of differentlengths associated with it. The second index can have just one window,or it can also have two, three, or more windows associated with it.Monitoring the entropy of the HRV signal, for example, could track theentropy in a 30 second window, a 24 hour window, and a 6 month window.

In one embodiment, the first index is a first autonomic index and thesecond index is a second autonomic index. In a further embodiment, thefirst autonomic index is a cardiovascular index or a respiratory index,and the second autonomic index is a cardiovascular index or arespiratory index.

In one embodiment, the first index is an autonomic index and the secondindex is a neurologic index. Exemplary autonomic indices include, butare not limited to, those derivable from cardiovascular signals,breathing signals, pupillary signals, skin signals, or blood pressure,among others. In one particular embodiment, the autonomic index is heartrate, values calculable from heart rate (such as magnitude and/or rateof change of heart rate, and heart rate variability, among others),heart beat wave morphology, and heart beat complex morphology (includingmeasures of premature ventricular contractions (PVCs)), among others.Signals relating to these particular indices can be detected by anyappropriate sensor, such as an R-wave detector or an electrocardiography(EKG) device, among others.

The definition of various indices as autonomic or neurologic, or variousautonomic indices as cardiovascular or respiratory, is to some extentarbitrary, though the present disclosure uses these terms in aconsistent manner apparent to the person of ordinary skill in the art.Specifically, the autonomic system, which is under brain (neurological)control, exerts (in a normal body) powerful influences on thecardiovascular, respiratory, and gastrointestinal systems. The integrityof these body systems is a condition for optimal brain (neurological)function. For simplicity and clarity, the term “autonomic” system orindex will encompass cardiovascular, respiratory, dermal (skin),pupillary, gastrointestinal systems or their indices.

Brain neurological signals may be derived from EEG, ECoG,magnetoencephalography, brain imaging methods and modalities, chemicalmethods, EMG, or accelerometry, among others. Body kinetic neurologicalsignals can be detected by electromyography, accelerometry, and/orinclinometry, or means for measuring force, among others. Cognitivesignals may be obtained via manual or automated tests andquestionnaires.

Exemplary neurological indices include, but are not limited to, thosederivable from electrical signals (EEG, evoked responses),chemical-metabolic signals, cognitive (relating to functional andcognitive decline, as well as risk of future decline) signals, andkinetic signals (relating to gait, posture, accessory movements, falls),hippocampus and entorhinal cortex volumes, basal forebrain nucleivolumes, and cortical thickness to determine the pattern and rate ofatrophy. Other techniques, such as deformation-based and voxel-basedmorphometry, structural and effective connectivity by using diffusiontensor imaging, tractography, functional magnetic resonance imaging andpositron emission tomography, may be employed to assess the state ofdisease. Other neurological signals (e.g. rate, amplitude and pattern ofspikes) such as those generated by the cranial nerves spinal cord,spinal roots or nerves, may be used to assess disease state.

Through the application of appropriate techniques to EEG, ECoG, EKG, orother biological signals recorded from epileptic brains, maximal seizureintensity (Si), duration (Sd), and extent of spread (Sc) may becomputed. These measures may be used to compute seizure severity (SS) bytransforming them (Si, Sd, Sc) into their corresponding percentiles Pi,Pd, and Pc and calculating their average: SS=(Pi+Pd+Pc)/3. Thesemeasures (Si, Sd, Sc) may be used without transformation or they may betransformed using for example natural logarithms. Seizure severity andthe time elapsed between seizures (interseizure interval) defined as thetime between the end of a seizure and the onset of the next one provideinsight into the status of a patient's epilepsy. For example, increasesin mean or median seizure severity and/or decreases in mean or medianinterseizure interval would indicate the disease has progressed.

Cognitive neurological indices may comprise measures of attention,simple or complex reaction time, verbal or spatial memory, executivefunctions, calculation, language, reasoning, visuo-spatial functions,evoked responses, EEG, MEG, or brain imaging (e.g., static (MRI) orfunctional (e.g., PET or fMRI)) among others. In one embodiment, theneurologic index may include one of more tests such as, a structuredclinical interview, Wechsler Adult Intelligence Scale (WAIS-III) butwill be updating to WAIS-IV Wechsler Memory Scale-Third Edition(WMS-III: Logical Memory I & II, Faces I & II, Spatial Span), CaliforniaVerbal Learning Test-2^(nd) Edition (CVLT-II), Rey-Osterreith ComplexFigure Test (ROCF), Continuous Visual Memory Test, Sentence RepetitionTest (Multilingual Aphasia Examination), Complex Ideational Material(Boston Diagnostic Aphasia Examination), Category Fluency Test,Controlled Oral Word Association (COWA), Boston Naming Test (BNT), WideRange Achievement Test-4^(th) Edition (WRAT-IV: Reading), Trail MakingTest (Part A & B), Wisconsin Card Sort Test (WCST), Ruff Figural FluencyTest (RFFT), Sensory Imperception Test, Finger-Tip Number Writing Test,Benton Facial Recognition Test, Grooved Pegboard Test, Finger TappingTest, Thumb-Finger Sequencing Test, Edinburgh Handedness Inventory,Minnesota Multiphasic Personality Inventory-2^(nd) Edition (If readinglevel ≧6^(th) grade; if not use Personality Assessment Inventory).

Responsiveness tests based on measurement of simple or complex reactiontimes, are the subject of copending patent application Ser. No.12/756,065, filed Apr. 7, 2010, which is hereby incorporated byreference herein.

In one particular embodiment, the neurological index is a measure ofresponsiveness or a measure of physical (in)stability, such as number,frequency, or severity of falls. Signals relating to these particularindices can be detected by any appropriate sensor, such as an externalresponsiveness testing device or an internal responsiveness testingdevice (such as one making use of an implantable sound device togenerate a tone or sound in proximity to the ear, an implantableaccelerometer to detect a physical motion, such as the movement of alimb or a tap on the skin at the accelerometer implant site), amongothers.

Psychiatric indices (including, but not limited to, mood, thoughts, andhallucinations), and quality of life indices are also subject tomeasurement in the present invention. Those skilled in the art know ofthe existence of clinically validated tools to assess quality of lifeand psychiatric status. The measurements provided by these tools may beused to automatically warn the patient or the caregivers of impendingpsychiatric decompensation or of high risk of suicide, so that anadverse or fatal outcome may be averted through timely intervention.

In one embodiment, the quality of life (QOL) factors may include one ormore of scales such as, but are not limited to: the generic scale forquality of life; the Psychological General Well-Being Scale (PGWB); theWHO-Five Well-Being Index (WHO-5); the Quality of Life in DepressionScale (QLDS); the Social Functioning Scale-36 (SF-36); the SocialFunctioning Scale-12 (SF-12); the Quality of Life Enjoyment andSatisfaction Questionnaire-Short Form (Q-LES-Q-SF); and the StreamlinedLongitudinal Interval Continuation Evaluation-Condensed Version(SLICE-C).

Alternatively or in addition, the QOL index is a health-related QOLindex indicative of the patient's morbidity or any comorbidities.

Psychiatric assessment may entail administration of one or more of thefollowing tests or scales: mini-mental state examination or Folsteintest, abbreviated mental test score, Millon Clinical MultiaxialInventory-III, psychometric tests such as the WISC or WAIS, MinnesotaMultiphasic Personality Inventory, child Behavior Checklist, the BeckDepression Inventory. Other tests are the NEO-PI, the 16 PF, the OPQ(Occupational Personality Questionnaire), the Five Factor PersonalityInventory-Children (FFPI-C.), which are based on the Big Five taxonomy.Additional tests include but are not limited to the Behaviour andSymptom Identification Scale (BASIS-32), the Beck Hopelessness Scale,the Bipolar Affective Disorder Dimension, the Scale CompositeInternational Diagnostic Interview, the Depression-Anxiety stress scale,the General Health Questionnaire, the InterSePT Scale for SuicidalThinking, the Kessler Psychological Distress scale, the Major (ICD-10)Depression Inventory Psychotic symptoms rating scale, the Psychologicalgeneral well-being index, and the suicide intent scale.

Cardiovascular autonomic indices may be tested with the so calledEwing's battery, which consists of three tests reflecting cardiovascularparasympathetic and two tests reflecting cardiovascular sympatheticfunction: Heart rate response to forced breathing; heart rate responseto the Valsalva maneuver; heart rate response to standing erect; bloodpressure response to standing, and blood pressure response to handgrip.Other tests include baroreflex sensitivity, sympathetic skin response,heart rate and blood pressure variation during normal and deepbreathing, maximum systolic blood pressure increase in isometric work,the Valsalva maneuver, or postural change, blood pressure response topostural changes including tilting, the 30:15 ratio of heart rateresponse to standing, and time domain parameters such as SDNN, PNN50,rMSDD, EKG morphology, EKG rhythm pattern, heart sounds, blood pressure,chest wall deflection, ejection fraction, heart size, ventricular wallthickness, and heart contractility, among others. These indices can bederived from signals detected by electrocardiography, blood pressuremonitors, a microphone, apexcardiography, or echocardiography, amongother techniques.

Respiratory autonomic signals, skin autonomic signals, temperatureautonomic signals, and the like can be detected, and indices (e.g.,rate, pattern, tidal volume, vital capacity, forced vital capacity, skinresistance, sweat production, tympanic temperature, rectal temperature,and core temperature, among others) derived therefrom, by techniques andapparatus known to the person of ordinary skill in the art.

Changes in catecholamines (e.g, epinephrine, serotonin) and inmetabolites (vanillyl mandelic acid, metanephrine) in blood, urine, orother bodily fluids, during resting conditions or exercise, or asfunctions of time of day may be also be measured to assess the integrityof the autonomic nervous system. Direct recording of efferentpostganglionic muscle sympathetic nerve traffic via microneurography andapplication of the regional norepinephrine spillover technique may bealso used as autonomic indices. A technique using electrodes positionedon the abdominal skin to record stomach contractions(electrogastrography) provides information about autonomic functionthrough measurement of the dominant frequency (power) of contractionsand classify them as normal (eugastria) or abnormal (bradygastria,tachygastria).

Changes in hormone levels in blood or other bodily fluids, duringresting conditions or exercise, or as functions of time of day may bealso be measured to assess the integrity of the endocrine system. Forexample, the human body has its highest melatonin levels between aboutmidnight and eight a.m.; variations in the time of highest melatoninlevels, or increases or decreases in the levels themselves, may reflectimpairment of the endocrine system.

Therapies may adversely impact any body system. The tests ormeasurements described above for assessment of autonomic, neurologic,psychiatric, or endocrine function described in multiple parts of thisspecification, may be used for identifying and quantifying adverseeffects of any type of therapy for any disease. Assessment of liver,bone marrow, kidney, or skin may be performed with any of the existingblood (e.g liver enzymes, blood hemogram, creatinine, BUN, etc.),radiologic/imaging (liver or kidney ultrasound), or histologic (e.g.biopsies of bone marrow, skin, liver or kidney) tests that are commonpractice in medicine.

In this invention, “adverse effects of therapy” encompasses any and allbody systems (e.g., neurological, autonomic, psychiatric, hepatic,renal, dermal, etc.) that may be negatively affected by any form oftherapy (e.g., electrical, pharmacologic, thermal, cognitive, etc). Itis remarked that autonomic and adverse effect of therapy indices sharein common several dermal (skin) indices (e.g. temperature; color,texture), the only difference being that skin resistance is exclusivelyan autonomic index.

Changes in a person's physical fitness encompasses long-term and/orglobal measures of activity, such as measures of physical fitness (e.g.,VO2max, etc.). Physical fitness may be defined as the capacity to carryout the day's activities, pursue recreational activities, and have thephysical capability to handle emergency situations. Physical fitness canbe measured using strength tests (e.g., One repetition max), speed andpower tests (e.g., 30 m sprint; standing vertical jump), endurance Tests(e.g., Balke 15 minute run), and flexibility tests (e.g., sit and reachtest).

In another embodiment, the index value may be derivable from one or morecranial nerve signals (e.g, spike frequency, amplitude, or pattern,among others). In yet another embodiment, the index value may bederivable from one or more autonomic nerve or ganglia signals (e.g,spike frequency, amplitude, or pattern, among others).

Seizures are powerful biological stressors and inductors of stressmarker indices and deplete the body of certain anti-oxidants, such asglutathione peroxidase. Exemplary stress marker indices comprise changes(direction, rate, and magnitude) in glucose, prolactin, cortisol,catecholamines, chromogranin A, free radicals or reactive oxygenspecies, lactic acid, blood gases, N-acetylaspartate, in the expressionof heat shock proteins, and in metabolites of any or all thereof. Forexample, a “cortisol parameter” refers to a stress marker index relatingto cortisol or a metabolite thereof, and a “catecholamine parameter”refers to a stress marker index relating to a catecholamine or ametabolite thereof. The concentration of certain compounds that protectfrom biological stress (e.g., dehydroepiandrosterone or its sulfateconjugate, glutathione peroxidase) or the body's total antioxidantcapacity may be also measured to determine if it is adequate and if notto increase it using commercially or naturally available antioxidants tostall disease progression. Stress marker index indices and antioxidantsmay be measured in brain (invasively and non-invasively), CSF, plasma,serum, erythrocytes, urine, and saliva, (e.g. alpha amylase).Corticotropin-releasing factor (CRF) and the related urocortin peptidesare other examples of stress markers.

The time window or space-state over which the various indices arequantified can have any desired duration, and if a second time window orspace-state is used, it can have any desired second duration. The firsttime window or space-state and the second time window or space-state canhave any relationship. The two time windows may be overlapping,partially overlapping, contiguous, or non-contiguous, and the secondtime window or space-state may be a subwindow of the first time windowor space-state. In other words, the second time window or space-statemay be fully overlapped by the first time window or space-state.

In another embodiment, the first time window or space-state and thesecond time window or space-state are non-contiguous. In other words,the first and second time window or space-states do not overlap andthere exists a temporal gap between them.

Embodiments of the present invention also comprise comparing the atleast one index to at least one reference value associated with the atleast one index. In addition, if at least one second index has beendetermined as described above, the method can comprise comparing the atleast one second index or marker to at least one second reference valueassociated with the at least one second index.

The reference values can be preselected, selected from a finite set ofpredetermined options, or can be dynamically recalculated duringperformance of the method. They may be determined from the patient'shistory or from a set of normative data. For example, the referencevalues can be prior values of the index. For example, if the index valueis heart rate variability (HRV), the corresponding reference value canbe a single value defined by a physician in view of the patient's age,sex, fitness level, body mass index, physical fitness level at the timeof the measurement, initial disease state, or other values; it can be avalue chosen from a set of predetermined options relating to differenttypical initial disease states or the like; or it can be dynamicallyrecalculated, such as from an indicator of central tendency (e.g., amean, a median, or a percentile value) of HRV data over one or moretimescales, such as the past hour, day, week, month, or year, amongothers, to account for ultradian, circadian, catamenial, lunar, andseasonal variations.

In one embodiment, comparing the at least one first index to the atleast one first reference value, the at least one second index to the atleast one second reference value, or both comprises determining astatistical relationship (which may be linear or non-linear, positive ornegative) between the index or indices and the reference value orvalues. For example, the statistical relationship may be a number ofstandard deviations, percentile ranks, or the like between the referencevalue and the corresponding index.

The comparison may involve, when applicable, using spectral analysis,high order spectral analysis, detrended fluctuation analysis, fractalanalysis, multifractal analysis, correlation dimension, and combinationsthereof. For example, the comparison may involve determining the slopeof a trendline of data points, the shape of a curve of data points, thesmoothness of a set of data points, or an autocorrelation of a set ofdata points, among others.

The terms “index” refers to values, quantities, classes, categories oritems derived from signals (raw or processed). The term “reference”corresponds to quantities, classes, categories or items derived fromsignals (raw or processed) recorded from a subject in the past (recentor distant) or obtained from tables of comparable normative valuesobtained from other normal or diseased subjects. For example, the HRVcalculated from data collected over a period time ending in the presentday (the index) may be compared to HRV calculated from data collectedover an identical period of time 1 year earlier (the reference). Theindex as specified above may be also compared to HRV calculated fromsubjects that match the demographic and clinical characteristics (theother reference) of the subject in question. Determination about thestate of the subject's disease may be made by using either or both ofthe references. For example, a cognitive (e.g. verbal memory) or EEGindex (e.g., power in the alpha band) calculated from data collectedfrom a subjects over a period time ending in the present day (theindex), may be compared to verbal memory or alpha band power calculatedfrom data collected from over an identical period of time 1 year earlier(the reference) and to a third period of time, three years earlier.These indices as specified above may be also compared to verbal memoryand alpha band power obtained from subjects that match the demographicand clinical characteristics (the other reference) of the subject inquestion. Determination about the state of the subject's disease may bemade by using either or both of the references.

In one embodiment, comparing the at least one index to the at least onereference value comprises determining a non-linear relationship betweenthe index or indices and the reference value or values. For example, thenon-linear relationship may be related to a pattern matchingrelationship or a non-linear mathematic relationship between thereference value and the corresponding index.

Also, embodiments of the present invention comprises assessing a stateof a disease or a body system of the patient based on comparing the atleast one index to the at least one reference value. If at least onesecond index is received, assessing can be further based on comparingthe at least one second index to the at least one second referencevalue. For example, a second index and a third index can be received,and assessing can further based on comparing the second index to asecond reference value and comparing the third index to a thirdreference value.

In a further embodiment, embodiments of the present invention furthercomprise receiving at least one third autonomic index, neurologic index,stress marker index, psychiatric index, an endocrine index, an adverseeffect of therapy index, a physical fitness index, or quality of lifeindex of a patient over a third time window. In this further embodiment,the method also further comprises comparing the at least one third indexto at least one third reference value. In this further embodiment,assessing the state of the disease of the patient is based on comparingthe at least one first index to the at least one first reference valueassociated with the at least one first index, the at least one secondindex to the at least one second reference value associated with the atleast one second index, and the at least one third index to the at leastone third reference value associated with the at least one third index.

Although not limited to the following, exemplary systems capable ofimplementing embodiments of the present invention are described below.FIG. 3A depicts a stylized implantable medical system (IMD) 300 forimplementing one or more embodiments of the present invention. Anelectrical signal generator 310 is provided, having a main body 312comprising a case or shell with a header 316 for connecting to aninsulated, electrically conductive lead assembly 322. The generator 310is implanted in the patient's chest in a pocket or cavity formed by theimplanting surgeon just below the skin (indicated by a dotted line 345),similar to the implantation procedure for a pacemaker pulse generator.

A nerve electrode assembly 325, preferably comprising a plurality ofelectrodes having at least an electrode pair, is conductively connectedto the distal end of the lead assembly 322, which preferably comprises aplurality of lead wires (one wire for each electrode). Each electrode inthe electrode assembly 325 may operate independently or alternatively,may operate in conjunction with the other electrodes. In one embodiment,the electrode assembly 325 comprises at least a cathode and an anode. Inanother embodiment, the electrode assembly comprises one or moreunipolar electrodes.

Lead assembly 322 is attached at its proximal end to connectors on theheader 316 of generator 310. The electrode assembly 325 may besurgically coupled to the vagus nerve 327 in the patient's neck or atanother location, e.g., near the patient's diaphragm or at theesophagus/stomach junction. Other (or additional) cranial nerves such asthe trigeminal and/or glossopharyngeal nerves may also be used todeliver the electrical signal in particular alternative embodiments. Inone embodiment, the electrode assembly 325 comprises a bipolarstimulating electrode pair 326, 328 (i.e., a cathode and an anode).Suitable electrode assemblies are available from Cyberonics, Inc.,Houston, Tex., USA as the Model 302 electrode assembly. However, personsof skill in the art will appreciate that many electrode designs could beused in the present invention. In one embodiment, the two electrodes arewrapped about the vagus nerve, and the electrode assembly 325 may besecured to the vagus nerve 327 by a spiral anchoring tether 330 such asthat disclosed in U.S. Pat. No. 4,979,511 issued Dec. 25, 1990 to ReeseS. Terry, Jr. Lead assembly 322 may be secured, while retaining theability to flex with movement of the chest and neck, by a sutureconnection to nearby tissue (not shown).

In alternative embodiments, the electrode assembly 325 may comprisetemperature sensing elements, blood pressure sensing elements, and/orheart rate sensor elements. Other sensors for other body parameters mayalso be employed. Both passive and active stimulation may be combined ordelivered by a single IMD according to the present invention. Either orboth modes may be appropriate to treat a specific patient underobservation.

In alternative embodiments, the implantable medical device systemfurther comprises an electrical stimulator comprising an autonomicsignal sensor 360 a (not to scale) adapted to be coupled to a body part,such as an internal organ 380 (FIG. 3B) or a neurologic signal sensor360 n (also not to scale) adapted to record (either non-invasively orinvasively) from a portion of the nervous system, such as the frontalcortex 390 (FIG. 3C) or another region of the brain. The physician canselect precise locations for coupling to the internal organ 380 orfrontal cortex 390 (or other portion of the nervous system) based on hisor her observations of the patient's medical condition, among othervalues. In various embodiments, the implantable medical device systemmay comprise one, two, or three of the IMD 300, the autonomic signalsensor 360 a, and the neurologic signal sensor 360 n.

The electrical pulse generator 310 may be programmed with an externaldevice (ED) such as computer 350 using programming software known in theart. A programming wand 355 may be coupled to the computer 350 as partof the ED to facilitate radio frequency (RF) communication between thecomputer 350 and the pulse generator 310. The programming wand 355 andcomputer 350 permit non-invasive communication with the generator 310after the latter is implanted. In systems where the computer 350 usesone or more channels in the Medical Implant Communications Service(MICS) bandwidths, the programming wand 355 may be omitted to permitmore convenient communication directly between the computer 350 and thepulse generator 310.

Turning now to FIG. 4, a block diagram depiction of a medical device 400is provided, in accordance with one illustrative embodiment of thepresent invention.

In some embodiments, the medical device 400 may be implantable (such asimplantable electrical signal generator 310 from FIG. 3), while in otherembodiments the medical device 400 may be completely external to thebody of the patient.

The medical device 400 (such as generator 310 from FIG. 3) may comprisea controller 410 capable of controlling various aspects of the operationof the medical device 400. The controller 410 is capable of receivinginternal data or external data, and in one embodiment, is capable ofcausing a therapy unit 420 (FIG. 4) to generate and deliver anelectrical signal to target tissues of the patient's body for treating amedical condition. For example, the controller 410 may receive manualinstructions from an operator externally, or may cause the electricalsignal to be generated and delivered based on internal calculations andprogramming. The controller 410 is capable of affecting substantiallyall functions of the medical device 400.

The controller 410 may comprise various components, such as a processor415, a memory 417, etc. The processor 415 may comprise one or moremicrocontrollers, microprocessors, etc., capable of performing variousexecutions of software components. The memory 417 may comprise variousmemory portions where a number of types of data (e.g., internal data,external data instructions, software codes, status data, diagnosticdata, etc.) may be stored. The memory 417 may comprise one or more ofrandom access memory (RAM), dynamic random access memory (DRAM),electrically erasable programmable read-only memory (EEPROM), flashmemory, etc.

As stated above, in one embodiment, the medical device 400 may alsocomprise a therapy unit 420 capable of generating and deliveringelectrical signals to one or more electrodes 326, 328 via leads 401(FIG. 4). A lead assembly such as lead assembly 322 (FIG. 3) may becoupled to the medical device 400. Therapy may be delivered to the leads401 comprising the lead assembly 322 by the therapy unit 420 based uponinstructions from the controller 410. The therapy unit 420 may comprisevarious circuitry, such as electrical signal generators, impedancecontrol circuitry to control the impedance “seen” by the leads, andother circuitry that receives instructions relating to the delivery ofthe electrical signal to tissue. The therapy unit 420 is capable ofdelivering electrical signals over the leads 401 comprising the leadassembly 322. As should be apparent, in certain embodiments, the medicaldevice 400 does not comprise a therapy unit 420, lead assembly 322, orleads 401.

In other embodiments, a lead 401 is operatively coupled to an electrode,wherein the electrode is adapted to couple to at least one of a portionof a brain structure of the patient, a cranial nerve of a patient, aspinal cord of a patient, a sympathetic nerve structure of the patient,or a peripheral nerve of the patient.

The medical device 400 may also comprise a power supply 430. The powersupply 430 may comprise a battery, voltage regulators, capacitors, etc.,to provide power for the operation of the medical device 400, includingdelivering the therapeutic electrical signal. The power supply 430comprises a power source that in some embodiments may be rechargeable.In other embodiments, a non-rechargeable power source may be used. Thepower supply 430 provides power for the operation of the medical device400, including electronic operations and the electrical signalgeneration and delivery functions. The power supply 430 may comprise alithium/thionyl chloride cell or a lithium/carbon monofluoride (LiCFx)cell if the medical device 400 is implantable, or may compriseconventional watch or 2V batteries for external (i.e., non-implantable)embodiments. Other battery types known in the art of medical devices mayalso be used.

The medical device 400 may also comprise a communication unit 460capable of facilitating communications between the medical device 400and various devices. In particular, the communication unit 460 iscapable of providing transmission and reception of electronic signals toand from an monitoring unit 470, such as a handheld computer or PDA thatcan communicate with the medical device 400 wirelessely or by cable. Thecommunication unit 460 may include hardware, software, firmware, or anycombination thereof.

The medical device 400 may also comprise one or more sensor(s) 360 a,360 n coupled via sensor lead(s) 411 to the medical device 400.Sensor(s) 360 a are capable of receiving signals related to an autonomicindex, such as the patient's heart beat, blood pressure, and/ortemperature, among others, and delivering the signals to the medicaldevice 400. Sensor(s) 360 n are capable of receiving signals related toa neurologic index, and delivering the signals to the medical device400. In one embodiment, the sensor(s) 360 a, 360 n may be the same asimplanted electrode(s) 326, 328 (FIG. 3). In other embodiments, thesensor(s) 360 a, 360 n are separate structures that may be placed on thepatient's skin, such as over the patient's heart or elsewhere on thepatient's body. The sensor(s) 360 a, 360 n and accompanying leads may beconsidered an interface for the medical device 400 to receive, e.g., atleast one of autonomic data, neurologic data, or stress data, such asfrom the sensors 360 a, 360 n.

Exemplary sensor(s) 360 a include electrocardiography (EKG) devices,accelerometers, inclinometers, pupillometers, face or body temperaturemonitors, skin resistance monitors, and/or sound and pressure sensors,among others known to the person of ordinary skill in the art having thebenefit of the present disclosure.

Alternatively or in addition to sensors 360, the medical device 400 cancomprise at least one interface (not shown) capable of receiving datarelating to at least one index. For example, the interface can receivedata comprising index values. Alternatively or in addition, theinterface can receive data further processible by other components ofthe medical device 400.

The medical device may also comprise at least one of an autonomic indexdetermination unit 465 capable of determining at least one autonomicindex, a neurologic index determination unit 475 capable of determiningat least one neurologic index, a stress marker index determination unit477 capable of determining at least one stress marker index, apsychiatric index determination unit 479 capable of determining at leastone psychiatric index, an endocrine index determination unit 481 capableof determining at least one endocrine index, an adverse effect oftherapy index determination unit 482 capable of determining at least oneadverse effect of therapy index, or a quality of life (QOL) indexdetermination unit 485 capable of determining at least one quality oflife index. If present, the autonomic index determination unit 465 canreceive signals related to an autonomic index delivered to the medicaldevice 400 and, from them, determine an autonomic index. The autonomicindex determination unit 465 will be discussed in more detail below.Similarly, if present, the neurologic index determination unit 475 canreceive signals related to a neurologic index delivered to the medicaldevice 400 and, from them, determine a neurologic index. The neurologicindex determination unit 475 will be discussed in more detail below.Similarly, if present, the QOL index determination unit 485 can receivesignals related to a QOL index delivered to the medical device 400, suchas through the communication unit 460 and, from them, determine a QOLindex. In one embodiment, the signals related to a QOL index are sentfrom a remote device 492 that is capable of gathering such signals. Inanother embodiment, the QOL index determination unit 485 is located inremote device 492.

Also, similarly, if present, the stress marker index determination unit477 can receive signals related to a stress marker index delivered tothe medical device 400 and, from them, determine a stress marker index.Also, if present, the psychiatric index determination unit 479 canreceive signals related to an psychiatric index delivered to the medicaldevice 400 and, from them, determine an psychiatric index. Similarly, ifpresent, the endocrine index determination unit 481 can determine atleast one endocrine index and/or the adverse effect of therapy indexdetermination unit 482 can determine at least one adverse effect oftherapy index. The stress marker index determination unit 477,psychiatric index determination unit 479, endocrine index determinationunit 481, and one adverse effect of therapy index determination unit 482are discussed in more detail elsewhere herein.

The medical device 400 can also comprise an index comparison unit 495capable of comparing at least one index with at least one referencevalue. The reference value may be stored in the memory 417, in a localdatabase unit 455, a database unit 450, or a remote device 492. Theindex comparison unit 495 will be discussed in more detail below.

The medical device 400 can also comprise a assessment unit 487 capableof assessing a state of a disease of a patient based on at least oneoutput of the index comparison unit.

The medical device 400 can also comprise a warning unit 489 capable ofproviding a warning signal to the patient, a physician, or a caregiverif assessing indicates disease progression. In one embodiment, thewarning signal is proportional to at least one of a magnitude of achange of a progression, a rate of change of a disease progression, or acorrelation of the index value to life span.

The medical device 400 can also comprise a therapy unit adapted todeliver a therapy for the disease to a patient. For example, the medicaldevice 400 can comprise a therapy unit 420 and related hardware, such aslead(s) 401 and electrode(s) 326, 328.

Although not shown, the medical device 400 can comprise an acute diseasestate detection unit adapted to detect an acute disease state in thepatient. For example, the acute disease state detection unit can beadapted to detect an epileptic event. Common epileptic events of concernare, for example, clinical seizures, subclinical seizures, loss ofconsciousness, falls to the ground, cognitive impairment during andfollowing a seizure, prolonged confusional states, bodily injuries,alterations in heart, respiratory and in other functions under autonomiccontrol, sudden unexpected death, psychosis, depression, suicide,osteoporosis, obesity, and reproductive dysfunction. Exemplary acutedisease state detection units are known to the person of ordinary skillin the art and can be included in the medical device 400 as a matter ofroutine experimentation for those of ordinary skill in the art havingthe benefit of the present disclosure.

FIG. 5 shows a medical device system similar to that shown in FIG. 4,but with several elements located in an external device not implanted inthe patient. Specifically, FIG. 5 depicts a medical device system withthe following elements located in an external disease state unit: theautonomic index determination unit 465, the neurologic indexdetermination unit 475, the stress marker index determination unit 477,the psychiatric index determination unit 479, the endocrine indexdetermination unit 481, the adverse effect of therapy indexdetermination unit 482, the QOL index determination unit 485, the indexcomparison unit 495, and the assessment unit 487 are located in anexternal disease state unit. Housing these elements in an externaldisease state unit may permit use of more complex analysis tools andalgorithms because an externally unit generally can have a fastermicroprocessor (which consume more power and generate more heat), morememory, and AC power or larger batteries than an implanted device. Forexample, this embodiment of FIG. 5 may be useful if the calculationsperformable by the determination modules 465, 475, 477, 479, 485 or theunits 495, 487 are so complex and/or dependent on such a large number ofdata lookups (e.g., in a local database unit 455 or a database unit 450)that performing the calculations in the medical device 400 would consumetoo much power or generate too much heat.

Turning to FIG. 6, an autonomic index determination unit 465 is shown inmore detail. The autonomic index determination unit 465 can comprise acardiovascular signal unit 612 capable of processing at least onecardiovascular indication received from sensor(s) 360 a. Alternativelyor in addition, the autonomic index determination unit 465 can comprisea respiratory signal unit 614 capable of processing at least onerespiratory indication received from sensor(s) 360 a. Alternatively orin addition, the autonomic index determination unit 465 can comprise ablood parameter signal unit 623 capable of processing at least one bloodparameter indication (e.g., blood glucose, blood pH, etc). Alternativelyor in addition, the autonomic index determination unit 465 can comprisea temperature signal unit 616 capable of processing at least onetemperature indication received from sensor(s) 360 a. Alternatively orin addition, the autonomic index determination unit 465 can comprise anoptic signal unit 618 capable of processing at least one opticindication received from sensor(s) 360 a. Alternatively or in addition,the autonomic index determination unit 465 can comprise a chemicalsignal unit 620 capable of processing at least one body chemicalindication received from sensor(s) 360 a. Alternatively or in addition,the autonomic index determination unit 465 can comprise a hormone signalunit 622 capable of processing at least one hormone indication receivedfrom sensor(s) 360 a. Alternatively or in addition, the autonomic indexdetermination unit 465 can comprise one or more other autonomic signalunit(s) 624, such as a skin resistance signal unit.

The autonomic index determination unit 465 can also comprise anautonomic data processing unit 630. The autonomic data processing unit630 can perform any filtering, noise reduction, amplification, or otherappropriate processing of the data received by the signal units 612-624desired by the person of ordinary skill in the art prior to calculationof the autonomic index.

The autonomic index determination unit 465 can also comprise anautonomic index calculation unit 640. The autonomic index calculationunit 640 can calculate an autonomic index from the data passed by theautonomic data processing unit 630.

For example, the autonomic index calculation unit 640 may calculate theheart rate, a change in the heart rate, the speed of change in heartrate, blood pressure, heart sounds, heart rhythm, heartbeat wavemorphology, heartbeat complex morphology, or the shape of the deflectionof the thoracic wall as the heart apex beats against it, among others,from cardiovascular data received by cardiovascular signal unit 612.

For another example, the autonomic index calculation unit 640 maycalculate the respiration (breath) rate, respiration pattern, airflowvelocity, respiration amplitude (tidal volume), oxygen saturation,arterial gas concentrations, or blood pH, among others, from respiratorydata received by respiratory signal unit 614.

For still another example, the autonomic index calculation unit 640 maycalculate a change in the skin temperature or skin resistance of a partof the patient's face or a change in the core temperature of thepatient, from temperature data received by temperature signal unit 616.

Turning to FIG. 7, an exemplary embodiment of a neurologic indexdetermination unit 475 is shown. The neurologic index determination unit475 can comprise at least one of a neuro-electrical signal unit 712capable of processing at least one neuro-electrical signal received froma sensor 360 n; a neuro-chemical signal unit 714 capable of processingat least one neuro-chemical signal received from a sensor 360 n; aneuro-electrochemical signal unit 716 capable of processing at least oneneuro-electrochemical signal received from a sensor 360 n; or acognitive signal unit 720 capable of processing at least one cognitiveindication received from a sensor 360 n or another device, such as aremote device 492.

In one embodiment, the cognitive signal unit comprises at least one of acognitive aptitude determination unit 720 a capable of processing atleast one cognitive aptitude indication; an attention aptitudedetermination unit 720 b capable of processing at least one attentionaptitude indication; a memory aptitude determination unit 720 c capableof processing at least one memory indication; a language aptitudedetermination unit 720 d capable of processing at least one languageindication; a visual/spatial aptitude determination unit 720 e capableof processing at least one visual/spatial indication; a kineticcapability determination unit 720 f capable of processing at least onekinetic indication; one or more other neurologic factor determinationunit(s) 720 g; or a responsiveness determination unit 720 h.

The neurologic index determination unit 475 can also comprise aneurologic data processing unit 730. The neurologic data processing unit730 can perform any filtering, noise reduction, amplification, or otherappropriate processing of the data received by the signal units 712-720g desired by the person of ordinary skill in the art prior tocalculation of the neurologic index.

The neurologic index determination unit 475 can also comprise aneurologic index calculation unit 740. The neurologic index calculationunit 740 can calculate a neurologic index from the data passed by theneurologic data processing unit 730.

For example, the neurologic index calculation unit 740 may calculate abrain index, such as those determinable from signals yielded by an EEG,ECoG, or depth electrode (i.e., a deep brain electrode) as sensor(s) 360n, as received by neuro-electrical signal unit 712, neuro-chemicalsignal unit 714, and/or neuro-electrochemical signal unit 716 and,optionally, further processed by neurologic data processing unit 730.

The brain index can also be calculated using other neurological signals.For example, sensor(s) 360 n can detect spikes in neurons or axons inthe brain and spinal cord including central structures and pathways withautonomic control or modulatory capabilities, cranial nerves (e.g.,vagus nerve), autonomic ganglia or nerves and peripheral nerves.Sensor(s) 360 n can also detect neural imaging or brain imaging signalsincluding, for example: Functional Magnetic Resonance Imaging (fMRI),Magnetoencephalography (MEG), Positron Emission Tomography (PET),Event-Related Optical Signal (EROS), and Diffuse Optical Imaging (DOI)).Other imaging techniques such as voltage-senstive dyes, ultrasound,infra-red, near infra-red and other forms of thermography. Qualitativeor descriptive and quantitative (e.g. volumetrics) data obtained fromdevices that are not part of this system (e.g., MRI equipment) may beuploaded and stored into this system for assessing disease state.

For another example, the neurologic index calculation unit 740 maycalculate a body kinetic index, such as the body's (or of a portionthereof such as an arm or a leg) acceleration, direction, position,smoothness, amplitude, or force of movements, and whether there areextraneous or abnormal body oscillations during resting conditions ormovement. The body kinetic index may be determinable byelectromyography, a mechanogram, an accelerometer, and/or aninclinometer as sensor(s) 360 n, as received by kinetic capabilitydetermination unit 720 f, and, optionally, further processed byneurologic data processing unit 730.

Kinetic indices are voluntary or involuntary motor acts that provideinsight into the functional state of the nervous system and are thusclassified as a neurologic index. The ability to perform movements: a)in any direction; b) do it smoothly and with precision so that forexample, a target (e.g. putting a key into its hole) may be met in thefirst attempt or handwriting is legible; c) changing direction to avoidcolliding with an object interposed on its path to a target andre-adjusting the trajectory to reach the original target; and d) withadaptive force and discriminations so to be able to pick a penny off aflat surface and also lift heavy objects. The acceleration and velocityspeed, direction and smoothness may be quantified using tools such as3-D accelerometers among others.

Even though physical fitness indices depend to some extent on theintegrity of kinetic indices, in this invention they are considered asdistinct from kinetic indices. Physical fitness indices are used toassess physical fitness through certain measures as described herein. Aperson who leads a sedentary life is physically unfit but may havenormal kinetic indices.

FIG. 8 shows a kinetic capability determination unit 720 f in moredetail. The kinetic capability determination unit 720 f can be capableof receiving at least one of an accelerometer signal, an inclinometersignal, a movement signal, or a dynamometer (force) signal viaaccelerometer signal unit 812, inclinometer signal unit 814, movementsignal unit 816, or dynamometer signal unit 818, respectively. From theat least one of the accelerometer signal, the inclinometer signal, themovement signal, or a dynamometer signal, one or more of movement dataor falls data can be calculated by movement data calculation unit 822 orfalls data calculation unit 824, respectively. The calculated movementdata and/or falls data can be processed by kinetic signal processingunit 830, and thereafter, kinetic data calculated by kinetic datacalculation unit 840.

Turning to FIG. 9, an exemplary embodiment of a stress marker indexdetermination unit 477 is shown. The stress marker index determinationunit 477 can comprise at least one signal unit 912, capable of receivinga signal as described above from which a stress marker index can bederived, such as a cortisol parameter unit 920 a, a catecholamineparameter signal unit 920 b, and/or another stress marker parameter unit920 c.

The stress marker index determination unit 477 can also comprise astress marker index data processing unit 930. The stress marker indexdata processing unit 930 can perform any filtering, noise reduction,amplification, or other appropriate processing of the data received bythe signal unit 912 desired by the person of ordinary skill in the artprior to calculation of the stress marker index.

The stress marker index determination unit 477 can also comprise astress marker index calculation unit 940. The stress marker indexcalculation unit 940 can calculate a stress marker index from the datapassed by the stress marker index processing unit 930. For example, thestress marker index calculation unit 940 may calculate a stress markerindex as received by signal unit 912 and, optionally, further processedby stress marker index data processing unit 930.

Turning to FIG. 10, an exemplary embodiment of a psychiatric indexdetermination unit 479 is shown. The psychiatric index determinationunit 479 can comprise at least one signal unit 1012, capable ofreceiving a signal as described above from which a psychiatric index canbe derived. For example, the psychiatric index determination unit 479can comprise a psychiatric signal unit 1020, comprising one or more of athought determination unit 1020 a, a mood determination unit 1020 b, ora judgment determination unit 1020 c. The various determination units1020 a-c can use tests or scales discussed above to make adetermination, e.g., by administering a test known to the person ofordinary skill in the art to provide information regarding the subject'sthought, mood, or judgment, or receiving the results of such a test froman external source.

The psychiatric index determination unit 479 can also comprise apsychiatric index data processing unit 1030. The psychiatric index dataprocessing unit 1030 can perform any filtering, noise reduction,amplification, or other appropriate processing of the data received bythe signal unit 1012 desired by the person of ordinary skill in the artprior to calculation of the psychiatric index.

The psychiatric index determination unit 479 can also comprise apsychiatric index calculation unit 1040. The psychiatric indexcalculation unit 1040 can calculate a psychiatric index from the datapassed by the psychiatric index processing unit 1030.

For example, the psychiatric index calculation unit 1040 may calculate apsychiatric index as received by signal unit 1012 and, optionally,further processed by psychiatric index data processing unit 1030.

Turning to FIG. 11, an exemplary embodiment of an endocrine indexdetermination unit 481 is shown. The endocrine index determination unit481 can comprise at least one signal unit 1112, capable of receiving asignal as described above from which an endocrine index can be derived.In a particular embodiment, as depicted, the endocrine indexdetermination unit 481 can comprise a hormone signal unit 722, asdescribed above.

The endocrine index determination unit 481 can also comprise anendocrine index data processing unit 1130. The endocrine index dataprocessing unit 1130 can perform any filtering, noise reduction,amplification, or other appropriate processing of the data received bythe signal unit(s) 1112, 722 desired by the person of ordinary skill inthe art prior to calculation of the endocrine index.

The endocrine index determination unit 481 can also comprise anendocrine index calculation unit 1140. The endocrine index calculationunit 1140 can calculate an endocrine index from the data passed by theendocrine index processing unit 1130.

For example, the endocrine index calculation unit 1140 may calculate anendocrine index as received by signal unit(s) 1112, 722 and, optionally,further processed by endocrine index data processing unit 1130.

Turning to FIG. 12 an exemplary embodiment of an adverse effect oftherapy index determination unit 482 is shown. The adverse effect oftherapy index determination unit 482 can comprise at least one signalunit 1212, capable of receiving a signal as described above from whichan adverse effect of therapy index can be derived. In a particularembodiment, as depicted, the adverse effect of therapy determinationunit 482 can comprise one or more of a liver signal unit 1220, a bonemarrow signal unit 1222, a kidney signal unit 1224, or a skin signalunit signal unit 1226.

The adverse effect of therapy index determination unit 482 can alsocomprise an adverse effect of therapy index data processing unit 1230.The adverse effect of therapy index data processing unit 1230 canperform any filtering, noise reduction, amplification, or otherappropriate processing of the data received by the signal unit(s)1212-1226 desired by the person of ordinary skill in the art prior tocalculation of the adverse effect of therapy index.

The adverse effect of therapy index determination unit 482 can alsocomprise an adverse effect of therapy index calculation unit 1240. Theadverse effect of therapy index calculation unit 1240 can calculate anadverse effect of therapy index from the data passed by the adverseeffect of therapy index processing unit 1230.

For example, the adverse effect of therapy index calculation unit 1240may calculate an adverse effect of therapy index as received by signalunit(s) 1212-1226 and, optionally, further processed by adverse effectof therapy index data processing unit 1230.

Turning to FIG. 13, a block diagram of an index comparison unit 495 isdepicted. The index comparison unit 495 comprises an index datainterface 1310, which receives index information from one or more of theindex determination units 465, 475, 485, 477, and 479; an index datalookup unit 1320, which looks up a reference value for the index from alookup table; and a reference value to index comparison unit 1330, whichcompares the determined index value from units 465-485 to the referenceindex value returned by index data lookup unit 1320.

Turning to FIG. 14, a block diagram of an assessment unit 487 isdepicted. The assessment unit 487 receives comparison information fromindex comparison unit 495 and performs an assessment of at least onedisease state, at least one comorbidity, or both. The assessment unit487 contains an assessment processing unit 1410 that processes thecomparison information in view of one or more stored or otherwiseaccessible assessment criteria returned by assessment criteria unit1420. The assessment can be performed in real-time (without substantialdelay between performing the assessment and taking any prior actionreferred to herein) or off-line (involving calculations making use ofdata stored for some length of time). The assessment processing unit1410 yields an assessment. If the assessment unit 487 assesses a diseasestate, the output can comprise at least one of disease stability,disease progression, disease regression, or a finding that a diseasestate cannot be determined with a sufficient degree of confidence. Ifthe assessment unit 487 assesses a state of a body system of a patient,the output can comprise at least one of body system stability, bodysystem improvement, body system decline, or a finding that a body systemof the system cannot be determined with a sufficient degree ofconfidence. Exemplary body systems include, but are not limited to, anautonomic system, a neurologic system, a psychiatric system, anendocrine system, a hepatic system, a bone marrow system, a renalsystem, and a skin system. The assessment unit 487 can then store or logits assessment in a memory, provide an output to the patient, acaregiver, or a physician, or the like. Alternatively or in addition,one or more of the indices considered in making the assessment can alsobe stored or logged.

In a particular embodiment, the output of the assessment can comprisequantitative data relating to the state of the disease or the bodysystem. For example, in one embodiment, the output can comprise at leastone of a magnitude of a change of a progression, a magnitude of a changeof a regression, a rate of change of a progression, or a rate of changeof a regression, a magnitude of a change of an improvement, a magnitudeof a change of a decline, a rate of change of an improvement, or a rateof change of a decline. Alternatively or in addition, an output of anassessment of a disease state can comprise identifying new comorbiditiesnot previously identified. These data can be used to assess the overallstate of health of the subject and, when analyzed in the context ofquality of life index value, provide an assessment of the patient's wellbeing.

Regardless of its content, the output can be any form of audio, visual,or other communication. Exemplary outputs include, but are not limitedto, text, graphics, video, animation, a sound tone or tones, andmelodies, among others. The outputs can be sent to any device capable ofpresenting them to a user, such as a telephone, a handheld device, acomputer, a television, or a loudspeaker, among others.

Turning to FIG. 15, a block diagram of a forecast (or prognosis) unit1500 is depicted. The forecast (or prognosis) unit comprises a forecastdata receiving module 1510 capable of receiving information from one ormore of the assessment unit 487, one or more index determination units465, 475, 477, 479, or 485, one or more index comparison units 495, or amemory 417 storing prior outputs of such a unit, and forecast (orprognosis) estimation and issuance module 1520 capable of estimatingfrom the received data a future state of the disease, wherein theforecast comprises a disease stability, a disease progression, a diseaseregression, and/or a state of the body system, wherein the forecastcomprises a body system stability, a body system improvement, a bodysystem decline, or a finding that no forecast can be made. In a furtherembodiment, wherein the forecast is of disease progression, the forecastcomprises at least one of a risk of an increased magnitude of change ofprogression, a risk of an increased rate of change of progression, or arisk of emergence of one or more comorbidities associated with thedisease. These data can be used to issue a prognosis for a state ofhealth of patient. Forecasts or prognoses may be based on qualitative,semiquantitative, or qualitative measures obtained using conventionalforecasting methods, such as those used in the fields of geophysics,finance, population dynamics including epidemics, material sciences(e.g. predicting material fatigue), and dynamical control systems. Whenappropriate, clinical judgment may be applied alone or in the frame ofBayesian statistics.

In one embodiment, a medical device system is provided. The medicaldevice system can comprise an interface to receive at least one ofautonomic data, neurologic data, and quality of life data. The interfacecan be similar to that described above.

The medical device system can comprise at least one of an autonomicindex determination unit capable of determining at least one autonomicindex, a neurologic index determination capable of determining at leastone neurologic index unit, or a quality of life index determination unitcapable of determining at least one quality of life index. The indexdetermination unit(s) can be similar to those described above.

The medical device system can comprise an index comparison unit capableof comparing at least one index with at least one reference value. Theindex comparison unit can be similar to those described above.

The medical device system can comprise a assessment unit capable ofassessing a state of a disease or a body system of a patient based on atleast one output of the index comparison unit. The assessment unit canbe similar to those described above.

In one embodiment, the medical device system further comprises a therapyunit adapted to deliver a therapy for the disease to a patient. Thetherapy unit may administer therapy in a contingent (“closed-loop”)manner in response to a particular manifestation of the disease, or in anon-contingent (“open-loop”) manner without reference to at least oneparticular manifestation of the disease. A combination of contingent andnon-contingent therapies may be also administered. Further, when therapyis administered in a contingent manner, a particular therapy regimen maybe selected in response to particular findings output by the assessmentunit. For example, if the assessment unit finds the patient's diseasestate is worsening, one or more therapy parameters may be modified toprovide a more intensive therapy. For example, if the therapy iselectrical stimulation of a neural tissue of a patient, the on-time,amplitude, and/or frequency of stimulation may be increased, and/or theoff-time decreased, to provide a more intensive therapy. Therapy type(e.g., electrical, pharmacological, thermal, cognitive, etc.), andparameters including time or timing of delivery may be tailored to statevariations in the probability of occurrence or severity of amanifestation of the disease.

In another embodiment, the medical device system further comprises anacute disease state detection unit adapted to detect an acute diseasestate in the patient. By “acute disease state” is meant a particularmanifestation of the disease that is more intense or debilitating thanthe patient's baseline presentation. For example, if the disease isepilepsy, the “acute disease state” can be an epileptic event, such as aseizure. In this example, the acute disease state detection unit isadapted to detect an epileptic event.

In another embodiment, the medical device system further comprises adisease warning unit adapted to provide a warning signal of change in adisease state, of an impending acute disease state, or a change in abody system parameter. For example, a warning signal may be provided ifthere is a change in a cardiovascular index that is deemed serious,exceeds a predetermined value, or if there is an impending seizure. Thiswarning signal may be delivered to the subject, a caregiver, or to anemergency medical unit.

In one embodiment, the warning signal is proportional to at least one ofa magnitude of a change of a disease progression, a rate of change of adisease progression, or a correlation of the index value to life span(deterioration in an autonomic cardiac parameter is more likely tonegatively impact life span than in a neurologic index, such ascognitive decline). Alternatively or in addition, in one embodiment, thewarning signal is proportional to at least one of a magnitude of achange of a body system decline or a rate of change of a body systemdecline. For example, the warning signal may comprise a tonecharacterized by a pitch and/or a volume, and the warning signal maybecome higher in pitch and/or louder in proportion to a magnitude orrate of change of a disease state or a body system decline.

In addition to components of the medical device 400 described above, animplantable medical system may comprise a storage unit to store anindication of at least one of seizure or an increased risk of a seizure.The storage unit may be the memory 417 of the medical device 400,another storage unit of the medical device 400, or an external database,such as the local database unit 455 or a remote database unit 450. Thestorage unit can allow retention of a history of index values and/orassessments of disease state and/or comorbidity. For example, the outputfrom this storage unit can be sent to the assessment unit 487 toquantify disease state and determine if there is progression,stabilization, or regression of the disease, or if a determinationcannot be made. Alternatively or in addition, the output from thisstorage unit can be sent to the assessment unit 487 to quantify a stateof a body system of a patient. The medical device 400 may communicatethe indication via the communications unit 460. Alternatively or inaddition to an external database, the medical device 400 may be adaptedto communicate the indication to at least one of a patient, a caregiver,or a healthcare provider.

In various embodiments, one or more of the units or modules describedabove may be located in a monitoring unit 470 or a remote device 492,with communications between that unit or module and a unit or modulelocated in the medical device 400 taking place via communication unit460. For example, in one embodiment, one or more of the interface, theautonomic index determination unit 465, the neurologic indexdetermination unit 475, the stress marker index determination unit 477,the psychiatric index determination unit 479, an endocrine indexdetermination unit 481, an adverse effect of therapy index determinationunit 482, a physical fitness index determination unit 483, the qualityof life index determination unit 485, the index comparison unit 495,and/or the assessment unit 487 may be external to the medical device400, e.g., in a monitoring unit 470. Locating one or more of theforegoing units outside the medical device 400 may be advantageous ifthe calculation(s) is/are computationally intensive, in order to reduceenergy expenditure and heat generation in the medical device 400 or toexpedite calculation.

The monitoring unit 470 may be a device that is capable of transmittingand receiving data to and from the medical device 400. In oneembodiment, the monitoring unit 470 is a computer system capable ofexecuting a data-acquisition program. The monitoring unit 470 may becontrolled by a healthcare provider, such as a physician, at a basestation in, for example, a doctor's office. In alternative embodiments,the monitoring unit 470 may be controlled by a patient in a systemproviding less interactive communication with the medical device 400than another monitoring unit 470 controlled by a healthcare provider.Whether controlled by the patient or by a healthcare provider, themonitoring unit 470 may be a computer, preferably a handheld computer orPDA, but may alternatively comprise any other device that is capable ofelectronic communications and programming, e.g., hand-held computersystem, a PC computer system, a laptop computer system, a server, apersonal digital assistant (PDA), an Apple-based computer system, acellular telephone, etc. The monitoring unit 470 may download variousparameters and program software into the medical device 400 forprogramming the operation of the medical device, and may also receiveand upload various status conditions and other data from the medicaldevice 400. Communications between the monitoring unit 470 and thecommunication unit 460 in the medical device 400 may occur via awireless or other type of communication, represented generally by line477 in FIG. 4. This may occur using, e.g., wand 355 (FIG. 3) tocommunicate by RF energy with an implantable signal generator 310.Alternatively, the wand may be omitted in some systems, e.g., systems inwhich the MD 400 is non-implantable, or implantable systems in whichmonitoring unit 470 and MD 400 operate in the MICS bandwidths.

In one embodiment, the monitoring unit 470 may comprise a local databaseunit 455. Optionally or alternatively, the monitoring unit 470 may alsobe coupled to a database unit 450, which may be separate from monitoringunit 470 (e.g., a centralized database wirelessly linked to a handheldmonitoring unit 470). The database unit 450 and/or the local databaseunit 455 are capable of storing various patient data. These data maycomprise patient parameter data acquired from a patient's body, therapyparameter data, seizure severity data, therapeutic efficacy data, and/ordisease state assessment data. The database unit 450 and/or the localdatabase unit 455 may comprise data for a plurality of patients, and maybe organized and stored in a variety of manners, such as in date format,severity of disease format, etc. The database unit 450 and/or the localdatabase unit 455 may be relational databases in one embodiment. Aphysician may perform various patient management functions (e.g.,programming parameters for a responsive therapy and/or settingthresholds for one or more detection parameters) using the monitoringunit 470, which may include obtaining and/or analyzing data from themedical device 400 and/or data from the database unit 450 and/or thelocal database unit 455. The database unit 450 and/or the local databaseunit 455 may store various patient data.

One or more of the blocks illustrated in the block diagrams of themedical device 400 in FIGS. 4-12 may comprise hardware units, softwareunits, firmware units, or any combination thereof. Additionally, one ormore blocks illustrated in FIGS. 4-12 may be combined with other blocks,which may represent circuit hardware units, software algorithms, etc.Additionally, any number of the circuitry or software units associatedwith the various blocks illustrated in FIGS. 4-12 may be combined into aprogrammable device, such as a field programmable gate array (FPGA), anASIC device, etc.

In one embodiment, the present invention may include coupling of atleast one electrode to each of two or more cranial nerves. (In thiscontext, two or more cranial nerves mean two or more nerves havingdifferent names or numerical designations, and do not refer to the leftand right versions of a particular nerve). In one embodiment, at leastone electrode may be coupled to either or both vagus nerves or a branchof either or both vagus nerves. The term “operatively” coupled mayinclude directly or indirectly coupling. Each of the nerves in thisembodiment or others involving two or more cranial nerves may bestimulated according to particular activation modalities that may beindependent between the two nerves.

Although not so limited, in one embodiment, the method further comprisesapplying a therapy to a neural tissue of the patient, in response to theassessing. In a further embodiment, the therapy is an electricaltherapy. In a further embodiment, the neural tissue is a cranial nerve,such as the vagus nerve.

Therapies using electrical currents or fields to provide a therapy to apatient (electrotherapy) are beneficial for certain neurologicaldisorders, such as epilepsy. Implantable medical devices have beeneffectively used to deliver therapeutic electrical stimulation tovarious portions of the human body (e.g., the vagus nerve) for treatingepilepsy. As used herein, “stimulation,” “neurostimulation,”“stimulation signal,” “therapeutic signal,” or “neurostimulation signal”refers to the direct or indirect application of an electrical,mechanical, magnetic, electro-magnetic, photonic, acoustic, cognitive,and/or chemical signal to a neural structure in the patient's body. Thesignal is an exogenous signal that is distinct from the endogenouselectro-chemical, activity inherent to the patient's body and theenvironment. In other words, the stimulation signal (whether electrical,mechanical, magnetic, electro-magnetic, photonic, acoustic, cognitive,and/or chemical in nature) applied to a cranial nerve or to othernervous tissue structure in the present invention is a signal appliedfrom a medical device, e.g., a neurostimulator. Alternatively or inaddition, electrochemical activity inherent to the patient's body orbrain may be tapped, harnessed or modified (as in the case of cognitivetherapy) to treat a disease manifestation or the disease its elf.

A “therapeutic signal” refers to a stimulation signal delivered to apatient's body with the intent of treating a medical condition through asuppressing (blocking) or modulating effect to neural tissue. The effectof a stimulation signal on neuronal activity may be suppressing ormodulating; however, for simplicity, the terms “stimulating”,suppressing and modulating, and variants thereof, are sometimes usedinterchangeably herein. In general, however, the delivery of anexogenous signal itself refers to “stimulation” of the neural structure,while the effects of that signal, if any, on the electrical activity ofthe neural structure are properly referred to as suppression ormodulation.

Depending upon myriad factors such as the history (recent and distant)of the nervous system, stimulation parameters and time of day, to name afew, the effects of stimulation upon the neural tissue may be excitatoryor inhibitory, facilitatory or disfacilitatory and may suppress, enhanceor leave unaltered, neuronal activity. One can witness a suppressingeffect when, for example, a stimulation signal applied to neural tissueprevents or ameliorates abnormal neurological activity (e.g., epilepticseizures). This suppressing effect takes place through multiplemechanisms, as described in the foregeoing articles. Suppression ofabnormal neural activity is a threshold or suprathreshold process andthe temporal scale over which it may occur is usually on the order oftens or hundreds of milliseconds. Modulation of abnormal or undesirableneural activity, unlike suppression is a “sub-threshold” process in thespatio-temporal domain that may summate and result under certainconditions, in threshold or suprathreshold neural events. The temporalscale of modulation is much longer than that of suppression,encompassing seconds to months or even years. In addition to inhibitionor dysfacilitation, modification of neural activity may occur by waveannihilation (a concept borrowed from wave mechanics) or through phaseresetting.

Electrotherapy may be provided by implanting an electrical device, i.e.,an implantable medical device (IMD), inside a patient's body stimulationof a nervous tissue, such as a cranial nerve. Generally, electrotherapysignals that suppress or modulate neural activity are delivered by theIMD via one or more leads or wirelessly. When applicable, the leadsgenerally terminate at their distal ends in one or more electrodes, andthe electrodes, in turn, are coupled to tissue in the patient's body.For example, a number of electrodes may be attached to various points ofa nerve or other tissue inside a human body for delivery of aneurostimulation signal.

While contingent (also referred to as “closed-loop,” “active,” or“feedback” stimulation (i.e., electrotherapy applied in response tosensed information, such as heart rate)) stimulation schemes have beenproposed, non-contingent, programmed periodic stimulation is theprevailing modality. For example, vagus nerve stimulation for thetreatment of epilepsy usually involves a series of grouped electricalpulses defined by an “on-time” (such as 30 sec) and an “off-time” (suchas 5 min) This type of stimulation is also referred to as “open-loop,”“passive,” or “non-feedback” stimulation. Each sequence of pulses duringan on-time may be referred to as a “pulse burst.” The burst is followedby the off-time period in which no signals are applied to the nerve.During the on-time, electrical pulses of a defined electrical current(e.g., 0.5-2.0 milliamps) and pulse width (e.g., 0.25-1.0 milliseconds)are delivered at a defined frequency (e.g., 20-30 Hz) for a certainduration (e.g., 10-60 seconds). The on-time and off-time parameterstogether define a duty cycle, which is the ratio of the on-time to thecombination of the on-time and off-time, and which describes thepercentage of time that the electrical signal is applied to the nerve.

In open-loop VNS, the on-time and off-time may be programmed to definean intermittent pattern in which a repeating series of electrical pulsebursts are generated and applied to a cranial nerve such as the vagusnerve. The off-time is provided to minimize adverse effects and conservepower. If the off-time is set at zero, the electrical signal inopen-loop VNS may provide continuous stimulation to the vagus nerve.Alternatively, the off time may be as long as one day or more, in whichcase the pulse bursts are provided only once per day or at even longerintervals. Typically, however, the ratio of “off-time” to “on-time” mayrange from about 0.5 to about 10.

In addition to the on-time and off-time, the other parameters definingthe electrical signal in VNS may be programmed over a range of values.The pulse width for the pulses in a pulse burst of open-loop VNS may beset to a value not greater than about 1 msec, such as about 250-500μsec, and the number of pulses in a pulse burst is typically set byprogramming a frequency in a range of about 20-300 Hz (i.e., 20 pulsesper second to 300 pulses per second). A non-uniform frequency may alsobe used. Frequency may be altered during a pulse burst by either afrequency sweep from a low frequency to a high frequency, or vice versa.Alternatively, the timing between adjacent individual signals within aburst may be randomly changed such that two adjacent signals may begenerated at any frequency within a range of frequencies.

Returning to systems for providing cranial nerve stimulation, such asthat shown in FIG. 3, and as stated above, alternatively or in additionto a responsive treatment, if any, cranial nerve stimulation may beprovided on a continuous basis to alleviate chronic aspects of thepatient's medical disorder. Where cranial nerve stimulation is providedbased solely on programmed off-times and on-times, the stimulation maybe referred to as passive, inactive, open-loop, non-feedback, ornon-contingent stimulation. In contrast, stimulation may be triggered byone or more feedback loops according to changes in the body or brain ofthe patient. This stimulation may be referred to as active, closed-loop,feedback-loop, or contingent stimulation. In one embodiment,feedback-loop stimulation may be manually-triggered stimulation, inwhich the patient manually causes the activation of a pulse burstoutside of the programmed on-time/off-time cycle at a time of thepatient's choosing, for example, in response to a sensation of animpending seizure. The patient may manually activate an implantablesignal generator 310 to stimulate the cranial nerve, such as vagus nerve327, to treat an acute episode of a medical condition, e.g., a seizure.The patient may also be permitted to alter the intensity of the signalsapplied to the cranial nerve within limits established by the physician.

Patient activation of a medical device 300 may involve use of anexternal control magnet for operating a reed switch in an implanteddevice, for example. Certain other techniques of manual and automaticactivation of implantable medical devices are disclosed in U.S. Pat. No.5,304,206 to Baker, Jr., et al. (“the '206 patent”). According to the'206 patent, means for manually activating or deactivating theelectrical signal generator 310 may include a sensor such aspiezoelectric element mounted to the inner surface of the generator caseand adapted to detect light taps by the patient on the implant site. Oneor more taps applied in fast sequence to the skin above the location ofthe electrical signal generator 310 in the patient's body may beprogrammed into the implanted medical device 300 as a signal forintensification of the electrical signal. Two taps spaced apart by aslightly longer duration of time may be programmed into the medicaldevice 300 to indicate a desire to de-intensify the electrical signal.The patient may be given limited control over operation of the device toan extent which may be determined by the program or entered by theattending physician. The patient may also activate the medical device300 using other suitable techniques or apparatus.

In one embodiment, the medical device 400 may also be capable ofdetecting a manual input from the patient. The manual input may includea magnetic signal input, a tap input, a wireless data input to themedical device 400, etc.

The above methods may be performed by a computer readable programstorage device encoded with instructions that, when executed by acomputer, perform the method described herein.

In one embodiment, the disease is obesity. As depicted in FIG. 16, withthe directionality of each arrow indicating an amplifying effect,obesity substantially increases the patient's risk of developingdiabetes mellitus, arterial hypertension, hyperlipidemia and obstructivesleep apnea, while shortening life span and degrading quality of life.Arterial hypertension, diabetes and hyperlipidemia, in turn, accelerateatherosclerosis, further increasing the risks for myocardial infarction,stroke, congestive heart failure, and avascular gangrene. Similarly,obstructive sleep apnea causes intractable arterial hypertension, atrialfibrillation, cognitive deterioration, depression, sexual dysfunction,and chronic headaches.

In one embodiment, the disease is epilepsy. Pharmaco-resistant seizuresare associated with an increase in mortality and morbidity rates(compared to the general population and to epileptics whose seizures arecontrolled by medications), eventual impairment of cognitive functionsand mental health, and markedly degraded quality of life for patientsand their families. Seizures may impair motor control, responsiveness toa wide class of stimuli, and other cognitive functions. Certainpharmacological agents used for treatment of epilepsy causeosteoporosis, reproductive dysfunction, liver and bone marrow damage,and in rare cases, death. FIG. 17 depicts relationships between epilepsyand some of its comorbidities, with the directionality of each arrowindicating an amplifying effect.

All of the methods and apparatuses disclosed and claimed herein may bemade and executed without undue experimentation in light of the presentdisclosure. While the methods and apparatus of this invention have beendescribed in terms of particular embodiments, it will be apparent tothose skilled in the art that variations may be applied to the methodsand apparatus and in the steps, or in the sequence of steps, of themethod described herein without departing from the concept, spirit, andscope of the invention, as defined by the appended claims. It should beespecially apparent that the principles of the invention may be appliedto selected cranial nerves other than, or in addition to, the vagusnerve to achieve particular results in treating patients havingepilepsy, depression, or other medical conditions.

In various embodiments, the present invention relates to the subjectmatter of the following numbered paragraphs:

1. A medical device system, comprising:

at least one of an autonomic index determination unit capable ofdetermining at least one autonomic index, a neurologic indexdetermination unit capable of determining at least one neurologic index,a stress marker index determination unit capable of determining at leastone stress marker index, a psychiatric index determination unit capableof determining at least one psychiatric index, an endocrine indexdetermination unit capable of determining at least one endocrine index,an adverse effect of therapy index determination unit capable ofdetermining at least one adverse effect of therapy index, a physicalfitness index determination unit capable of determining at least onephysical fitness index, or a quality of life index determination unitcapable of determining at least one quality of life index;

an index comparison unit capable of comparing at least one index with atleast one reference value;

a body system state assessment unit capable of assessing a state of abody system of a patient, wherein the body system comprises at least oneof an autonomic system, a neurologic system, a psychiatric system, anendocrine system, an hepatic system, a renal system, a bone marrowsystem, a skin system, or subsystems of the foregoing; and

an output unit capable of providing an output relating to theassessment, wherein the output comprises at least one of body systemstability, body system improvement, body system decline, or a findingthat a state of the body system cannot be determined.

2. The medical device system of numbered paragraph 1, further comprisinga disease state assessment unit capable of assessing a state of adisease, wherein the output comprises disease stability, diseaseprogression, disease regression, or a finding that a disease statecannot be determined.

3. The medical device system of numbered paragraph 2, furthercomprising:

a comorbidity identification unit adapted to identify a comorbidityassociated with the disease.

4. The medical device system of numbered paragraph 1, furthercomprising:

at least one interface capable of receiving at least one of an autonomicsignal, a neurologic signal, a stress marker signal, a psychiatricsignal, an endocrine signal, an adverse effect of therapy signal, aphysical fitness signal, or a quality of life signal of a patient.

5. The medical device system of numbered paragraph 1, furthercomprising:

a forecast unit capable of forecasting a state of the body system,wherein the forecast comprises a body system stability, a body systemimprovement, a body system decline, or a finding that no forecast can bemade.

6. The medical device system of numbered paragraph 1, furthercomprising:

a logging unit capable of logging one or more of the assessments orindices.

7. The medical device system of numbered paragraph 1, wherein theautonomic index determination unit comprises at least one of:

-   -   a cardiovascular indication processing unit,    -   a respiration indication processing unit,    -   a blood parameter indication processing unit,    -   a pupillary response indication processing unit,    -   a body temperature indication processing unit, or    -   a skin resistance indication processing unit; and

the neurologic index determination unit comprises at least one of:

-   -   an attention aptitude indication processing unit,    -   a responsiveness indication processing unit,    -   a memory indication processing unit,    -   a kinetic indication processing unit, or    -   a cognitive aptitude indication processing unit; and

the stress marker index determination unit comprises at least one of:

-   -   a cortisol parameter indication processing unit, or    -   a catecholamine parameter indication processing unit.

8. A medical device system, comprising:

an autonomic index determination unit capable of determining at leastone autonomic index;

a neurologic index determination unit capable of determining at leastone neurologic index;

an index comparison unit capable of comparing the at least one autonomicindex with at least one first reference value and the at least oneneurologic index with at least one second reference value;

an epilepsy disease state assessment unit capable of assessing a stateof an epilepsy disease; and

an output unit capable of providing an output relating to theassessment, wherein the output comprises at least one of diseasestability, disease progression, disease regression, or a finding that adisease state cannot be determined.

9. The medical device system of numbered paragraph 8, furthercomprising:

a warning unit adapted to provide a warning if the epilepsy diseasestate assessment unit yields an assessment of disease progression.

10. The medical device system of numbered paragraph 8, furthercomprising:

a therapy unit adapted to deliver a therapy for epilepsy to a patient.

11. The medical device system of numbered paragraph 8, furthercomprising:

at least one interface capable of receiving at least one of autonomicdata or neurologic data.

12. The medical device system of numbered paragraph 8, furthercomprising:

a forecast unit capable of forecasting a state of the disease, whereinthe forecast comprises a disease stability, a disease progression, adisease regression, or a finding that no forecast can be made.

13. The medical device system of numbered paragraph 8, furthercomprising:

a logging unit capable of logging one or more of the assessments orindices.

14. The medical device system of numbered paragraph 8, wherein theautonomic index determination unit comprises at least one of:

-   -   a cardiovascular indication processing unit,    -   a respiration indication processing unit,    -   a blood parameter indication processing unit,    -   a pupillary response indication processing unit,    -   a body temperature indication processing unit, or    -   a skin resistance indication processing unit; and

the neurologic index determination unit comprises at least one of:

-   -   an attention aptitude indication processing unit,    -   a responsiveness indication processing unit,    -   a memory indication processing unit,    -   a kinetic indication processing unit, or    -   a cognitive aptitude indication processing unit.

15. The medical device system of numbered paragraph 8, furthercomprising:

a comorbidity identification unit adapted to identify a comorbidityassociated with the disease.

16. A medical device system, comprising:

at least one assessment unit capable of assessing at least one of apatient's disease state, a quality of life, or a physical fitness,

at least one determination unit capable of determining at least one of adisease state assessment, a quality of life assessment, or a physicalfitness assessment;

at least one comparison unit capable of comparing the at least onedisease state assessment, quality of life assessment, or physicalfitness assessment to at least one reference value,

a disease state assessment unit capable of assessing at least one ofdisease state, quality of life, or physical fitness; and

an output unit capable of providing an output relating to an assessmentof the patient's health, wherein the output comprises disease stability,disease progression, disease regression, or a finding that a diseasestate cannot be determined.

101. A computer readable program storage unit encoded with instructionsthat, when executed by a computer, perform a method for assessing aprimary disease state and a body system impacted by the primary disease,comprising:

receiving at least a first index and a second index, each index relatingto at least one of an autonomic index, a neurologic index, a stressmarker index, a psychiatric index, an endocrine index, an adverse effectof therapy index, a physical fitness index, or a quality of life indexof a patient,

comparing the at least one first index to at least one first referencevalue associated with the at least one first index;

comparing the at least one second index to at least one second referencevalue associated with the at least one second index;

assessing a state of said primary disease of the patient based on thecomparing;

assessing a state of a body system of the patient based on the assessingthe state of the disease, wherein the body system comprises at least oneof an autonomic system, a neurologic system, a psychiatric system, anendocrine system, a hepatic system, a renal system, a bone marrowsystem, a skin system, or subsystems of the foregoing; and

providing an output relating to the assessment of the state of theprimary disease and the assessment of the state of the body system,wherein the output comprises at least one of disease stability, diseaseprogression, disease regression, or a finding that a disease statecannot be determined, and the output further comprises at least one ofbody system stability, body system improvement, body system decline, ora finding that a state of the body system cannot be determined.

102. The computer readable program storage unit of numbered paragraph101, wherein the method further comprises:

assessing a state of a second disease of the patient based on thecomparing, wherein the output further comprises at least one of diseasestability, disease progression, disease regression, or a finding that adisease state cannot be determined; and

assessing a state of a second body system of the patient based on thecomparing, wherein the body system comprises at least one of anautonomic system, a neurologic system, a psychiatric system, anendocrine system, a hepatic system, a renal system, a bone marrowsystem, a skin system, or subsystems of the foregoing, and the outputfurther comprises at least one of body system stability, body systemimprovement, body system decline, or a finding that a state of the bodysystem cannot be determined.

103. The computer readable program storage unit of numbered paragraph101, wherein the output comprises at least one of a magnitude of achange of a progression, a magnitude of a change of a regression, a rateof change of a progression, or a rate of change of a regression, amagnitude of a change of an improvement, a magnitude of a change of aregression, a rate of change of an improvement, or a rate of change of aregression.

104. The computer readable program storage unit of numbered paragraph101, wherein the at least one first index is at least one autonomicindex and the at least one second index is at least one neurologicindex.

105. The computer readable program storage unit of numbered paragraph104, wherein the at least one autonomic index comprises a cardiovascularparameter, a respiration parameter, a body temperature parameter, a skinresistance parameter, or two or more thereof; and

the at least one neurologic index comprises an attention aptitudeparameter, a responsiveness parameter, a memory parameter, a kineticparameter, a cognitive aptitude parameter, or two or more thereof.

106. The computer readable program storage unit of numbered paragraph101, wherein the disease is epilepsy.

107. The computer readable program storage unit of numbered paragraph101, wherein the method further comprises providing a warning signal tothe patient, a physician, or a caregiver if assessing indicates at leastone of disease progression or body system decline.

108. The computer readable program storage unit of numbered paragraph107, wherein the warning signal is proportional to at least one of amagnitude of a change of a progression, a rate of change of aprogression, a magnitude of a change of a body system decline, or a rateof change of a body system decline.

109. The computer readable program storage unit of numbered paragraph101, wherein the first index comprises a weighted composite of a firstplurality of autonomic indices, neurologic indices, stress markerindices, psychiatric indices, endocrine indices, adverse effect oftherapy indices, physical fitness indices, quality of life indices, ortwo or more thereof;

the second index comprises a weighted composite of a second plurality ofautonomic indices, neurologic indices, stress marker indices,psychiatric indices, endocrine indices, adverse effect of therapyindices, physical fitness indices, quality of life indices, or two ormore thereof;

or both.

110. The computer readable program storage unit of numbered paragraph101, wherein at least one of the first reference value or the secondreference value is based on the patient's history or on normative data.

111. The computer readable program storage unit of numbered paragraph101, wherein at least one of the first index or the second indexcomprises a measure of central tendency, a measure of dimensionality, ameasure of fractality, a measure of stationarity, a measure oflong-range dependency, a measure of clustering, a distribution ofmeasures of central tendency, a distribution of measures ofdimensionality, a distribution of measures of fractality, a distributionof measures of stationarity, a distribution of measures of long-rangedependency, a distribution of measures of clustering, or two or morethereof.

112. The computer readable program storage unit of numbered paragraph101, wherein the method further comprises forecasting a state of thedisease, wherein the forecast comprises a disease stability, a diseaseprogression, a disease regression, or a finding that no forecast can bemade.

113. The computer readable program storage unit of numbered paragraph112, wherein the forecast is of disease progression and the forecastcomprises at least one of a risk of an increased magnitude of change ofprogression, a risk of an increased rate of change of progression, or arisk of emergence of one or more comorbidities associated with thedisease.

114. The computer readable program storage unit of numbered paragraph101, wherein the method further comprises forecasting a state of thebody system, wherein the forecast comprises a body system stability, abody system improvement, a body system decline, or a finding that noforecast can be made.

115. The computer readable program storage unit of numbered paragraph101, wherein the assessment of the state of the disease comprisesidentifying one or more comorbidities associated with the disease.

116. A computer readable program storage unit encoded with instructionsthat, when executed by a computer, perform a method for assessing apatient's health, comprising:

receiving at least one assessment of at least one of a patient's diseasestate, a quality of life, or a physical fitness,

comparing the at least one assessment to at least one reference valueassociated with at least one previous assessment from the patient orwith normative data,

assessing at least one of disease state, quality of life, or physicalfitness based on the comparing; and

providing an output relating to an assessment of the patient's health,wherein the output comprises at least one of disease state stability,disease state progression, disease state regression, a finding that thedisease state cannot be determined, quality of life stability, qualityof life improvement, quality of life decline, a finding that the qualityof life cannot be determined, physical fitness stability, physicalfitness improvement, physical fitness decline, or a finding thatphysical fitness cannot be determined.

201. A medical device system, comprising:

at least one of an autonomic index determination unit capable ofdetermining at least one autonomic index, a neurologic indexdetermination unit capable of determining at least one neurologic index,a stress marker index determination unit capable of determining at leastone stress marker index, a psychiatric index determination unit capableof determining at least one psychiatric index, an endocrine indexdetermination unit capable of determining at least one endocrine index,an adverse effect of therapy index determination unit capable ofdetermining at least one adverse effect of therapy index, a physicalfitness index determination unit capable of determining at least onephysical fitness index, or a quality of life index determination unitcapable of determining at least one quality of life index;

an index comparison unit capable of comparing at least one first indexwith at least one first reference value associated with the at least onefirst index and comparing at least one second index with at least onesecond reference value associated with the at least one second index;

a body system state assessment unit capable of assessing a state of abody system of a patient, wherein the body system comprises at least oneof an autonomic system, a neurologic system, a psychiatric system, anendocrine system, a hepatic system, a renal system, a bone marrowsystem, a skin system, or subsystems of the foregoing;

a disease state assessment unit capable of assessing a state of adisease; and

an output unit capable of providing an output relating to theassessment, wherein the output comprises at least one of body systemstability, body system improvement, body system decline, or a findingthat a state of the body system cannot be determined, and the outputfurther comprises disease stability, disease progression, diseaseregression, or a finding that a disease state cannot be determined.

202. The medical device system of numbered paragraph 201, furthercomprising:

at least one interface capable of receiving at least one of an autonomicindex, a neurologic index, a stress marker index, a psychiatric index,an endocrine index, an adverse effect of therapy index, a physicalfitness index, or a quality of life index of a patient.

203. The medical device system of numbered paragraph 201, furthercomprising:

a forecast unit capable of forecasting at least one of a state of thedisease or a state of the body system, wherein the forecast comprises adisease stability, a disease progression, a disease regression, a bodysystem stability, a body system improvement, a body system decline, or afinding that no forecast can be made.

204. The medical device system of numbered paragraph 201, furthercomprising:

a logging unit capable of logging one or more of the assessments orindices.

205. The medical device system of numbered paragraph 201, wherein theautonomic index determination unit comprises at least one of:

-   -   a cardiovascular indication processing unit,    -   a respiration indication processing unit,    -   a blood parameter indication processing unit,    -   a pupillary response indication processing unit,    -   a body temperature indication processing unit, or    -   a skin resistance indication processing unit; and

the neurologic index determination unit comprises at least one of:

-   -   an attention aptitude indication processing unit,    -   a responsiveness indication processing unit,    -   a memory indication processing unit,    -   a kinetic indication processing unit, or    -   a cognitive aptitude indication processing unit; and

the stress marker index determination unit comprises at least one of:

-   -   a cortisol parameter indication processing unit, or    -   a catecholamine parameter indication processing unit.

206. The medical device system of numbered paragraph 201, furthercomprising:

a comorbidity identification unit adapted to identify a comorbidityassociated with the disease.

207. A medical device system, comprising:

at least one of an autonomic index determination unit capable ofdetermining at least one of a cardiovascular parameter, a respiratoryparameter, or an autonomic parameter of a patient; or a neurologic indexdetermination unit capable of determining at least one of aresponsiveness parameter or a kinetic parameter of the patient;

an index comparison unit capable of comparing the cardiovascularparameter with at least one first reference value, the respiratoryparameter with at least one second reference value, and the kineticparameter with at least one third reference value;

a real-time body system state assessment unit capable of assessing inreal-time a state of a body system of the patient, wherein the bodysystem comprises at least one of an autonomic system, a neurologicsystem, a psychiatric system, an endocrine system, a hepatic system, arenal system, a bone marrow system, a skin system, or subsystems of theforegoing;

a communication unit capable of sending at least one of the real-timeassessment, the at least one autonomic parameter, or the at least oneneurologic parameter to an off-line body system state assessment unit;

an off-line body system state assessment unit capable of (a) receivingthe at least one of the real-time assessment, the at least one autonomicparameter, or the at least one neurologic parameter; (b) receiving atleast one second index comprising at least one of an autonomic index, aneurologic index, a stress marker index, a psychiatric index, anendocrine index, an adverse effect of therapy index, a physical fitnessindex, or a quality of life index of a patient; and (c) assessingoff-line a state of a body system of the patient, wherein the bodysystem comprises at least one of an autonomic system, a neurologicsystem, a psychiatric system, an endocrine system, a hepatic system, arenal system, a bone marrow system, a skin system, or subsystems of theforegoing; and

an output unit capable of providing an output relating to at least oneof the real-time assessment or the off-line assessment, wherein theoutput relating to the real-time assessment comprises at least one ofbody system stability, body system improvement, body system decline, ora finding that a state of the body system cannot be determined, and theoutput relating to the off-line assessment comprises at least one ofbody system stability, body system improvement, body system decline, ora finding that a state of the body system cannot be determined.

208. The medical device system of numbered paragraph 207, wherein thecommunication unit is further capable of providing a warning signal tothe patient, a physician, or a caregiver if assessing in real-timeindicates body system decline.

209. The medical device system of numbered paragraph 208, wherein thewarning signal is proportional to at least one of a magnitude of achange in body system decline or a rate of change in body systemdecline.

210. The medical device system of numbered paragraph 208, furthercomprising a storage unit capable of storing at least one of thereal-time assessment, the off-line assessment, the at least oneautonomic index, the at least neurologic index, or the at least onesecond index.

211. A medical device system, comprising:

at least one assessment unit capable of assessing at least one of apatient's disease state, a quality of life, or a physical fitness,

at least one determination unit capable of determining at least one of adisease state assessment, a quality of life assessment, or a physicalfitness assessment;

at least one comparison unit capable of comparing the at least onedisease state assessment, quality of life assessment, or physicalfitness assessment to at least one reference value,

a disease state assessment unit capable of assessing at least one ofdisease state, quality of life, or physical fitness; and

an output unit capable of providing an output relating to an assessmentof the patient's health, wherein the output comprises disease statestability, disease state progression, disease state regression, afinding that the disease state cannot be determined, quality of lifestability, quality of life improvement, quality of life decline, afinding that the quality of life cannot be determined, physical fitnessstability, physical fitness improvement, physical fitness decline, or afinding that physical fitness cannot be determined.

The particular embodiments disclosed above are illustrative only as theinvention may be modified and practiced in different but equivalentmanners apparent to those skilled in the art having the benefit of theteachings herein. Furthermore, no limitations are intended to thedetails of construction or design herein shown other than as describedin the claims below. It is, therefore, evident that the particularembodiments disclosed above may be altered or modified and all suchvariations are considered within the scope and spirit of the invention.Accordingly, the protection sought herein is as set forth in the claimsbelow.

The invention claimed is:
 1. A non-transitory computer readable programstorage unit encoded with instructions that, when executed by acomputer, perform a method for assessing a body system for an emergenceof a comorbidity associated with a primary disease, comprising:receiving at least one of an autonomic index, a neurologic index, astress marker index, a psychiatric index, an endocrine index, or aquality of life index of a patient; comparing the at least one index toat least one reference value associated with the at least one index;assessing a susceptibility of a the body system to the emergence of thecomorbidity at least partially caused by the primary disease based onthe comparing, wherein the body system comprises at least one of anautonomic system, a neurologic system, a psychiatric system, anendocrine system, or subsystems of the foregoing; and providing anoutput relating to the assessing, wherein the output comprises at leastone of increased susceptibility, decreased susceptibility, stablesusceptibility, or a determination that a the susceptibility cannot bedetermined.
 2. The non-transitory computer readable program storage unitof claim 1, wherein the method further comprises assessing asusceptibility of a second body system to the comorbidity associatedwith the primary disease based on the comparing, wherein the second bodysystem comprises at least one of an autonomic system, a neurologicsystem, a psychiatric system, an endocrine system, or subsystems of theforegoing, and the output comprises at least one of second increasedsusceptibility, second decreased susceptibility, second stablesusceptibility, or a determination that the susceptibility cannot bedetermined.
 3. The non-transitory computer readable program storage unitof claim 1, wherein the output further comprises at least one of amagnitude of a change of an increased susceptibility, a magnitude of achange of a decreased susceptibility, a rate of change of an increasedsusceptibility, or a rate of change of a decreased susceptibility. 4.The non-transitory computer readable program storage unit of claim 1,wherein the method further comprises assessing a state of the primarydisease of the patient based on comparing at least one second index toat least one second reference value, wherein the output furthercomprises primary disease stability, primary disease progression,primary disease regression, or a finding that a primary disease statecannot be determined.
 5. The non-transitory computer readable programstorage unit of claim 4, wherein the output further comprisesidentifying at least a second comorbidity associated with the primarydisease.
 6. The non-transitory computer readable program storage unit ofclaim 4, wherein the method further comprises providing a warning signalto the patient, a physician, or a caregiver if the output comprisesprimary disease progression, primary disease regression, or primarydisease state indeterminability.
 7. The non-transitory computer readableprogram storage unit of claim 6, wherein the warning signal isproportional to at least one of a magnitude of a change of aprogression, a rate of change of a progression, or a role of the bodysystem in the overall health of the patient.
 8. The non-transitorycomputer readable program storage unit of claim 1, wherein the primarydisease is epilepsy; receiving comprises receiving at least oneautonomic index selected from a cardiovascular parameter, a respirationparameter, a body temperature parameter, a skin resistance parameter, ortwo or more thereof; and at least one neurologic index selected from anattention aptitude parameter, a responsiveness parameter, a memoryparameter, a kinetic parameter, a cognitive aptitude parameter, aquality of life parameter, or two or more thereof.
 9. The non-transitorycomputer readable program storage unit of claim 8, wherein receivingfurther comprises receiving at least one stress marker index selectedfrom a cortisol parameter, a catecholamine parameter, a lactic acidparameter, or two or more thereof.
 10. The non-transitory computerreadable program storage unit of claim 8, wherein the at least oneautonomic index comprises at least one of a cardiovascular parameter ora respiratory parameter, and the at least one neurologic index comprisesat least one of a responsiveness parameter or a kinetic parameter. 11.The non-transitory computer readable program storage unit of claim 1,wherein the method further comprises forecasting a state of the bodysystem, wherein the forecast comprises a body system stability, a bodysystem improvement, a body system deterioration, or a finding that noforecast can be made.
 12. The non-transitory computer readable programstorage unit of claim 1, wherein receiving comprises receiving aplurality of autonomic indices, neurologic indices, stress markerindices, psychiatric indices, endocrine indices, physical fitnessindices, quality of life indices, or two or more thereof; and the atleast one index comprises a weighted composite of the plurality ofautonomic indices, neurologic indices, stress marker indices,psychiatric indices, endocrine indices, physical fitness indices,quality of life indices, or two or more thereof.
 13. The non-transitorycomputer readable program storage unit of claim 1, wherein the at leastone reference value is based on the patient's index value history or onnormative data.
 14. The non-transitory computer readable program storageunit of claim 1, wherein the at least one index comprises a measure ofcentral tendency, a measure of dimensionality, a measure of fractality,a measure of stationarity, a measure of long-range dependency, a measureof clustering, a distribution of measures of central tendency, adistribution of measures of dimensionality, a distribution of measuresof fractality, a distribution of measures of stationarity, adistribution of measures of long-range dependency, a distribution ofmeasures of clustering, or two or more thereof.
 15. The non-transitorycomputer readable program storage unit of claim 1, wherein an output ofan increased susceptibility is indicative of a deterioration of thepatient's health, an output of a decreased susceptibility is indicativeof an improvement of the patient's health, an output of a stablesusceptibility is indicative of a stability of the patient's health, anoutput of deterioration in quality of life is indicative of adeterioration of the patient's mental health, an output of improvementin quality of life is indicative of an improvement of the patient'smental health, or an output of indeterminability of susceptibility isindicative of indeterminability of the patient's health.
 16. Thenon-transitory computer readable program storage unit of claim 4,wherein an output of primary disease deterioration is indicative of adeterioration of the patient's health, an output of primary diseaseimprovement is indicative of an improvement of the patient's health, anoutput of primary disease stability is indicative of a stability of thepatient's health, or an output of indeterminability of a primary diseaseis indicative of indeterminability of the patient's health.
 17. Thenon-transitory computer readable program storage unit of claim 12,further comprising determining the state of health of a patient usingsaid weighted composite index.
 18. A non-transitory computer readableprogram storage unit encoded with instructions that, when executed by acomputer, perform a method for assessing a body system for an emergenceof a comorbidity associated with a primary disease, comprising:receiving a first index selected from the group consisting of anautonomic index, a neurologic index, a stress marker index, apsychiatric index, an endocrine index, a physical fitness index, and aquality of life index of a patient; comparing the first index to atleast one reference value associated with the at least first index;assessing a susceptibility of a body system to the emergence of thecomorbidity at least partially caused by the primary disease based onthe comparing, wherein the body system comprises at least one of anautonomic system, a neurologic system, a psychiatric system, anendocrine system, or subsystems of the foregoing; assessing a state ofthe patient's health based on the assessing the susceptibility of thebody system to the emergence of the comorbidity; and providing an outputrelating to at least one of the assessment of the susceptibility of thebody system or the assessment of the state of the patient's health,wherein the output comprises at least one of increased susceptibility,decreased susceptibility, stable susceptibility, a determination thatthe susceptibility of the body system cannot be determined, a stablehealth state, a poorer health state, an improved health state, or afinding that the state of the patient's health cannot be determined. 19.A medical device system, comprising: a body index determination unitcapable of determining at least one of an autonomic index, at least oneneurologic index, at least one stress marker index, at least onepsychiatric index, at least one endocrine index, at least one adverseeffect of therapy index, at least one physical fitness index, or atleast one quality of life index; an index comparison unit capable ofcomparing at least one said index with at least one reference value; abody system susceptibility assessment unit capable of assessing asusceptibility of a body system to an emergence of a comorbidity atleast partially caused by a primary disease of a patient, wherein thebody system comprises at least one of an autonomic system, a neurologicsystem, a psychiatric system, an endocrine system, an hepatic system, arenal system, a bone marrow system, a skin system, or subsystems of theforegoing; and an output unit capable of providing an output relating tothe assessing, wherein the output comprises at least one of increasedsusceptibility, decreased susceptibility, stable susceptibility, or adetermination that a susceptibility of the body system cannot bedetermined.
 20. The non-transitory computer readable program storageunit of claim 1, wherein the method further comprises providing awarning signal to the patient, a physician, or a caregiver if the outputcomprises increased susceptibility or indeterminability ofsusceptibility.